NoSQL capabilities in Postgres are opening up new avenues for solving enterprise challenges without having to adopt new technologies that bring risk and instability to data management. EnterpriseDB has made it easier for developers to get started using the NoSQL capabilities in Postgres to develop Web 2.0 applications, deploying on Amazon with a new development environment featuring application frameworks, a web server and code samples.
This presentation covers how developers tap the powers of Postgres by addressing:
* How to use JSON and HSTORE side by side with ANSI SQL to create powerful, robust and scalable Web 2.0 data-driven applications
* Getting started with PGXDK (Postgres Extended Datatype Developer Kit), a free AMI that simplifies the development of Postgres-based applications that integrate NoSQL technologies with JSON and Python
* Code samples for writing applications with Postgres using dynamic new capabilities
If you would like to learn more about building your NoSQL Applications with Postgres please email sales@enterprisedb.com.
The proliferation of data from new data sources has generated greater demand for technologies that can handle and harvest value from unstructured data. Postgres is leading the movement of integrating unstructured data with the relational environment.
Postgres first added JSON and then enhanced it with new data types, functions and operators in recent releases. Now in beta is the JSONB “binary JSON” type. These advances follow the longstanding HStore data type added in 2006 to support key/value stores in Postgres. Now Postgres users can learn how to harness these capabilities to master unstructured data challenges with Postgres.
The presentation also covers:
* An overview of JSON data types and operators
* Examples of SELECT, UPDATE, etc
* An examination of performance considerations
For more information, please email sales@enterprisedb.com
Postgres has been proven to process document database workloads faster than MongoDB in benchmark testing. But there are multiple benefits to using Postgres over a specialized solution for such applications.
Application developers are finding new ways to combine schema-less data with traditional relational tables and deliver innovative applications faster while meeting evolving DevOps strategies and goals. Providing a single, ACID-compliant enterprise-ready database that can manage both structured and unstructured data supports the development process and reduces overall complexity.
Learn what Postgres can help you achieve. This covers:
-- Using JSON/JSONB and HSTORE to combine schema-less data with enterprise information
-- Build on existing skillsets while using web 2.0 development technologies
-- Reduce complexity that comes with using multiple heterogeneous platform and disparate application demands
-- New performance benchmark results showing Postgres outperforms MongdoDB
PgREST allows running Node.js modules inside PostgreSQL for building a JSON document store with existing relational data while being compatible with MongoDB APIs. It utilizes various PostgreSQL extensions and tools like PLV8, plv8x, and OneJS to enable JavaScript functionality within the database for code reuse across browser, server, and database applications. The document provides examples of using PgREST to load modules, run JSON queries, and integrate Node.js functionality directly inside the database.
PostgreSQL has kept up the momentum around JSON with version 9.4 featuring JSONB as demand for working with unstructured data continues to grow. In this talk delivered during Postgres Open 2014, Vibhor Kumar, principal systems engineer at EnterpriseDB, offered some scenarios for working with JSON in PostgreSQL and demonstrated performance metrics. This session also gave some instruction on how to use different operations and explored comparisons to BSON.
The document discusses using PostgreSQL as a NoSQL database. It introduces JSON and HSTORE data types for storing semi-structured and unstructured data. It provides examples of storing and querying JSON and HSTORE data. Performance tests show PostgreSQL can handle many NoSQL workloads faster than MongoDB. The document advocates for using PostgreSQL's "Not only SQL" capabilities rather than a NoSQL-only solution.
A powerful feature in Postgres called Foreign Data Wrappers lets end users integrate data from MongoDB, Hadoop and other solutions with their Postgres database and leverage it as single, seamless database using SQL.
Use of these features has skyrocketed since EDB released to the open source community new FDWs for MongoDB, Hadoop and MySQL that support both read and write capabilities. Now greatly enhanced, FDWs enable integrating data across disparate deployments to support new workloads, expanded development goals and harvesting greater value from data.
Target Audience: This presentation is intended for IT Professionals seeking to do more with Postgres in his every day projects and build new applications.
OrientDB vs Neo4j - and an introduction to NoSQL databasesCurtis Mosters
NoSQL databases are a good alternative to common SQL technologies. Here you get an introduction and comparison of SQL vs NoSQL. Furthermore we have a look on Graph databases and especially OrientDB vs Neo4j.
MongoDB is a document-oriented NoSQL database that provides polyglot persistence and multi-model capabilities. It supports document, graph, relational, and key-value data models through a single backend. MongoDB also provides tunable consistency levels, secondary indexing, aggregation capabilities, and multi-document ACID transactions. Mature drivers simplify application development, while MongoDB Atlas provides a fully managed cloud database service with high availability, security, and monitoring.
The proliferation of data from new data sources has generated greater demand for technologies that can handle and harvest value from unstructured data. Postgres is leading the movement of integrating unstructured data with the relational environment.
Postgres first added JSON and then enhanced it with new data types, functions and operators in recent releases. Now in beta is the JSONB “binary JSON” type. These advances follow the longstanding HStore data type added in 2006 to support key/value stores in Postgres. Now Postgres users can learn how to harness these capabilities to master unstructured data challenges with Postgres.
The presentation also covers:
* An overview of JSON data types and operators
* Examples of SELECT, UPDATE, etc
* An examination of performance considerations
For more information, please email sales@enterprisedb.com
Postgres has been proven to process document database workloads faster than MongoDB in benchmark testing. But there are multiple benefits to using Postgres over a specialized solution for such applications.
Application developers are finding new ways to combine schema-less data with traditional relational tables and deliver innovative applications faster while meeting evolving DevOps strategies and goals. Providing a single, ACID-compliant enterprise-ready database that can manage both structured and unstructured data supports the development process and reduces overall complexity.
Learn what Postgres can help you achieve. This covers:
-- Using JSON/JSONB and HSTORE to combine schema-less data with enterprise information
-- Build on existing skillsets while using web 2.0 development technologies
-- Reduce complexity that comes with using multiple heterogeneous platform and disparate application demands
-- New performance benchmark results showing Postgres outperforms MongdoDB
PgREST allows running Node.js modules inside PostgreSQL for building a JSON document store with existing relational data while being compatible with MongoDB APIs. It utilizes various PostgreSQL extensions and tools like PLV8, plv8x, and OneJS to enable JavaScript functionality within the database for code reuse across browser, server, and database applications. The document provides examples of using PgREST to load modules, run JSON queries, and integrate Node.js functionality directly inside the database.
PostgreSQL has kept up the momentum around JSON with version 9.4 featuring JSONB as demand for working with unstructured data continues to grow. In this talk delivered during Postgres Open 2014, Vibhor Kumar, principal systems engineer at EnterpriseDB, offered some scenarios for working with JSON in PostgreSQL and demonstrated performance metrics. This session also gave some instruction on how to use different operations and explored comparisons to BSON.
The document discusses using PostgreSQL as a NoSQL database. It introduces JSON and HSTORE data types for storing semi-structured and unstructured data. It provides examples of storing and querying JSON and HSTORE data. Performance tests show PostgreSQL can handle many NoSQL workloads faster than MongoDB. The document advocates for using PostgreSQL's "Not only SQL" capabilities rather than a NoSQL-only solution.
A powerful feature in Postgres called Foreign Data Wrappers lets end users integrate data from MongoDB, Hadoop and other solutions with their Postgres database and leverage it as single, seamless database using SQL.
Use of these features has skyrocketed since EDB released to the open source community new FDWs for MongoDB, Hadoop and MySQL that support both read and write capabilities. Now greatly enhanced, FDWs enable integrating data across disparate deployments to support new workloads, expanded development goals and harvesting greater value from data.
Target Audience: This presentation is intended for IT Professionals seeking to do more with Postgres in his every day projects and build new applications.
OrientDB vs Neo4j - and an introduction to NoSQL databasesCurtis Mosters
NoSQL databases are a good alternative to common SQL technologies. Here you get an introduction and comparison of SQL vs NoSQL. Furthermore we have a look on Graph databases and especially OrientDB vs Neo4j.
MongoDB is a document-oriented NoSQL database that provides polyglot persistence and multi-model capabilities. It supports document, graph, relational, and key-value data models through a single backend. MongoDB also provides tunable consistency levels, secondary indexing, aggregation capabilities, and multi-document ACID transactions. Mature drivers simplify application development, while MongoDB Atlas provides a fully managed cloud database service with high availability, security, and monitoring.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Find out which is faster, SQL or NoSQL, for traditional reporting tasks. Discover how you can optimise MongoDB aggregation pipelines and how to push complex computation down to the database.
This document summarizes a MongoDB webinar on advanced schema design patterns. It introduces common schema design patterns like attribute, subset, computed, and approximation patterns. It discusses how to use these patterns to address issues like large documents with many fields, working sets that don't fit in RAM, high CPU usage from repeated calculations, and changing schemas over time. The webinar provides examples of each pattern and encourages learning a common vocabulary for designing MongoDB schemas by applying these reusable patterns.
MongoDB Evenings DC: Get MEAN and Lean with Docker and KubernetesMongoDB
This document discusses running MongoDB and Kubernetes together to enable lean and agile development. It proposes using Docker containers to package applications and leverage tools like Kubernetes for deployment, management and scaling. Specifically, it recommends:
1) Using Docker to containerize applications and define deployment configurations.
2) Deploying to Kubernetes where services and replication controllers ensure high availability and scalability.
3) Treating databases specially by running them as "naked pods" assigned to labeled nodes with appropriate resources.
4) Demonstrating deployment of a sample MEAN stack application on Kubernetes with MongoDB and discussing future work around experimentation and blue/green deployments.
Introducing Azure DocumentDB - NoSQL, No ProblemAndrew Liu
Application developers support unprecedented rates of change – functionality must rapidly evolve to meet changing customer needs and to respond to competitive pressures while user populations can grow dramatically and unpredictably. To address these realities, developers are selecting document-oriented databases for schema flexibility, scalability and high performance data storage.
In this session, we will get hands on with Azure’s NoSQL document database service. Azure DocumentDB offers full indexing of JSON documents, SQL query capabilities and multi-document transactions. Learn how to get started with Azure DocumentDB and hear about some of the recent improvements to the service.
Media owners are turning to MongoDB to drive social interaction with their published content. The way customers consume information has changed and passive communication is no longer enough. They want to comment, share and engage with publishers and their community through a range of media types and via multiple channels whenever and wherever they are. There are serious challenges with taking this semi-structured and unstructured data and making it work in a traditional relational database. This webinar looks at how MongoDB’s schemaless design and document orientation gives organisation’s like the Guardian the flexibility to aggregate social content and scale out.
MongoDB provides a concise summary of sharding in MongoDB:
1) Collections can be sharded (partitioned) across multiple servers, with each document assigned to a single shard based on the shard key.
2) Shards are divided into chunks based on the shard key range. Chunk metadata is stored in config servers and cached by mongos processes.
3) A balancer process monitors chunk distribution and migrates chunks between shards to improve balance as data and chunks sizes change over time. This helps distribute load evenly across shards.
Webinar: Best Practices for Getting Started with MongoDBMongoDB
MongoDB adoption continues to grow at a record pace due to the significant enhancements in developer productivity and scalability that the database provides. Occasionally, however, organizations new to the technology make mistakes that limit their ability to leverage the significant advantages MongoDB provides. This webinar will discuss some of the common mistakes made by users when they first start working with MongoDB, how to identify when you've made those mistakes, and how to resolve them.
This tutorial will introduce the features of MongoDB by building a simple location-based application using MongoDB. The tutorial will cover the basics of MongoDB’s document model, query language, map-reduce framework and deployment architecture.
The tutorial will be divided into 5 sections:
Data modeling with MongoDB: documents, collections and databases
Querying your data: simple queries, geospatial queries, and text-searching
Writes and updates: using MongoDB’s atomic update modifiers
Trending and analytics: Using mapreduce and MongoDB’s aggregation framework
Deploying the sample application
Besides the knowledge to start building their own applications with MongoDB, attendees will finish the session with a working application they use to check into locations around Portland from any HTML5 enabled phone!
TUTORIAL PREREQUISITES
Each attendee should have a running version of MongoDB. Preferably the latest unstable release 2.1.x, but any install after 2.0 should be fine. You can dowload MongoDB at http://www.mongodb.org/downloads.
Instructions for installing MongoDB are at http://docs.mongodb.org/manual/installation/.
Additionally we will be building an app in Ruby. Ruby 1.9.3+ is required for this. The current latest version of ruby is 1.9.3-p194.
For windows download the http://rubyinstaller.org/
For OSX download http://unfiniti.com/software/mac/jewelrybox/
For linux most users should know how to for their own distributions.
We will be using the following GEMs and they MUST BE installed ahead of time so you can be ahead of the game and safe in the event that the Internet isn’t accommodating.
bson (1.6.4)
bson_ext (1.6.4)
haml (3.1.4)
mongo (1.6.4)
rack (1.4.1)
rack-protection (1.2.0)
rack shotgun (0.9)
sinatra (1.3.2)
tilt (1.3.3)
Prior ruby experience isn’t required for this. We will NOT be using rails for this app.
NoSQL Analytics: JSON Data Analysis and Acceleration in MongoDB WorldAjay Gupte
In analytics world, when you need to process many millions or billions of documents to generate a single report. Novel techniques have been developed for exploiting modern processor architecture (larger on-chip cache, SIMD processing, compression, vector processing, columnar approach). Now, this technology is available to process your large JSON data. This talk will discuss analysis of JSON data using advanced data warehousing techniques and make it simple and seamless for the application/tool developer.
MongoDB is the leading NoSQL database due to a plenitude of reasons, open source, general purpose, document oriented database supported by a large community and educational platform. It's horizontal scalability features allows this to fit in the operational big data scenarios where the business needs point to realtime analytics and ever-increasing data sets. This talk will focus on the usage of MongoDB for big data operational purposes and why it's ideal to be used in such scenarios. Also integration with other notable big data technology out there like Hadoop and BI tools.
Norberto Leite - Senior Solutions Architect, @MongoDB.
Mongo DB presentation during the Pentaho & Big Data Ecosystem - Live Seminar 2013
The document introduces MongoDB, an open-source document database that provides high performance, high availability, and easy scalability. MongoDB keeps data as JSON-like documents which allows for flexible schemas and is well-suited for applications that work with unstructured or semi-structured data. The document also discusses how MongoDB can be used in conjunction with Hadoop for large-scale data processing and analytics workloads that require more than just a document database.
This presentation reviews Postgres’ unsurpassed NoSQL capabilities, which include a very rich JSON data type, a key-value pair data type, and a SQL/MED-based virtual data integration capability to bridge between Postgres and many other databases. Marc Linster discusses NoSQL syntax, NoSQL performance, and SQL/NoSQL integration and implementation recommendations.
To listen to the recording visit EnterpriseDB.com > Resources > Webcasts > On Demand Webcasts.
If you have any questions, please email sales@enterprisedb.com
NoSQL Now: Postgres - The NoSQL Cake You Can EatDATAVERSITY
The path to creating a single view of your customers or your transactional systems is overflowing with high costs and complexity. Major vendors have built massive, million-dollar systems that are too expensive and too complicated for most. NoSQL-only solutions seem to have promise, but simply do not necessarily have what you need. Learn what Postgres can do for you that NoSQL-only solutions can't.
Using a NoSQL-only solution and dumping gigabytes of data from multiple disparate systems into gigantic documents is complicated. And it forces tough choices—group all data by customer, by transaction, or by policy? You must choose, and this can be a hard process for some organizations. And almost always, organizations later learn they need relationships among the data, which NoSQL-only solutions cannot support.
Postgres eliminates the complexity and the pain of creating a single view of the customer. With recent advances, Postgres can support semi-structured, unstructured and structured data in the same environment, employing relational qualities and ACID compliance.
During this presentation, Marc Linster, SVP Products & Services, will review: ·
How to do more with Postgres
Open source alternative to RDBMS and more...
The NoSQL Conundrum
Why do developers like NoSQL Only solutions?
Problems and fallacies of NoSQL (only)
Data Standards
Data Islands
NoSQL Data Models include data access paths
Not Only SQL - Technology Innovation on a Robust Platform
Document Store
See JSON Examples
360 Degree view of the customer
Data Integration
Postgres eliminates the complexity and the pain of creating a single view of the customer. With recent advances, Postgres can support semi-structured, unstructured and structured data in the same environment, employing relational qualities and ACID compliance.
This presentation reviews:
- How advances in Postgres enable it to match capabilities of NoSQL-only niche solutions·
- How the ETL process in Postgres is simple compared to undoing tables and schemas in order to transfer data to a NoSQL-only system
- How Foreign Data Wrappers – essentially pipelines between Postgres and other databases – work and how they help bridge the gap between disparate systems faster than an ETL process
Visit Enterprisedb.com and go to our Resources section, then Webcasts to listen to the presentation recording.
The document discusses how PostgreSQL can be used as both a relational and NoSQL database, allowing it to meet more development needs than NoSQL databases alone. It outlines PostgreSQL's support for JSON and key-value storage, allowing it to store hierarchical and schemaless data like NoSQL databases while also providing SQL capabilities. This hybrid approach avoids issues like data silos that can occur with only using NoSQL solutions.
NoSQL and Spatial Database Capabilities using PostgreSQLEDB
PostgreSQL is an object-relational database system. NoSQL on the other hand is a non-relational database and is document-oriented. Learn how the PostgreSQL database gives one the flexible options to combine NoSQL workloads with the relational query power by offering JSON data types. With PostgreSQL, new capabilities can be developed and plugged into the database as required.
Attend this webinar to learn:
- The new features and capabilities in PostgreSQL for new workloads, requiring greater flexibility in the data model
- NoSQL with JSON, Hstore and its performance and features for enterprises
- Spatial SQL - advanced features in PostGIS application with PostGIS extension
Application Development & Database Choices: Postgres Support for non Relation...EDB
This talk will cover the advanced features of PostgreSQL that make it the most-loved RDBMS by developers and a great choice for non-relational workloads.
This webinar will explore:
- Global adoption of Postgres
- Document-centric applications
- Geographic Information Systems (GIS)
- Business intelligence
- Central data centers
- Server-side languages
This document discusses using PostgreSQL and its extensions to integrate various data sources. It provides an overview of PostgreSQL's support for JSON, foreign data wrappers (FDWs), and examples of using MongoDB and Cassandra FDWs. Specifically, it covers:
- PostgreSQL's JSON operators and functions for querying and manipulating JSON data
- FDWs allow querying remote data sources like MongoDB, HDFS, and other databases as if they were local tables
- Demos of loading JSON data and using JSON operators, and connecting to MongoDB using the MongoDB FDW
- Examples of companies using MongoDB and Cassandra FDWs with PostgreSQL to integrate different data sources
JSON support in DB2 for z/OS
1. To illustrate JSON storage model in DB2 for z/OS
2. To introduce JSON SQL APIs features and examples
3. To compare JSON and XML support in DB2 for z/OS
Application development with Oracle NoSQL Database 3.0Anuj Sahni
The document introduces table-based data modeling features for Oracle NoSQL Database. It discusses using tables to simplify application data modeling with familiar concepts like tables and data types. Examples show how to model user and email data using tables, including defining the schema using DDL, querying the data using DML, and indexing the tables. The document also provides an example of modeling user and email data from an email client application to illustrate how to approach data modeling.
This document discusses MongoDB and the needs of Rivera Group, an IT services company. It notes that Rivera Group has been using MongoDB since 2012 to store large, multi-dimensional datasets with heavy read/write and audit requirements. The document outlines some of the challenges Rivera Group faces around indexing, aggregation, and flexibility in querying datasets.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Find out which is faster, SQL or NoSQL, for traditional reporting tasks. Discover how you can optimise MongoDB aggregation pipelines and how to push complex computation down to the database.
This document summarizes a MongoDB webinar on advanced schema design patterns. It introduces common schema design patterns like attribute, subset, computed, and approximation patterns. It discusses how to use these patterns to address issues like large documents with many fields, working sets that don't fit in RAM, high CPU usage from repeated calculations, and changing schemas over time. The webinar provides examples of each pattern and encourages learning a common vocabulary for designing MongoDB schemas by applying these reusable patterns.
MongoDB Evenings DC: Get MEAN and Lean with Docker and KubernetesMongoDB
This document discusses running MongoDB and Kubernetes together to enable lean and agile development. It proposes using Docker containers to package applications and leverage tools like Kubernetes for deployment, management and scaling. Specifically, it recommends:
1) Using Docker to containerize applications and define deployment configurations.
2) Deploying to Kubernetes where services and replication controllers ensure high availability and scalability.
3) Treating databases specially by running them as "naked pods" assigned to labeled nodes with appropriate resources.
4) Demonstrating deployment of a sample MEAN stack application on Kubernetes with MongoDB and discussing future work around experimentation and blue/green deployments.
Introducing Azure DocumentDB - NoSQL, No ProblemAndrew Liu
Application developers support unprecedented rates of change – functionality must rapidly evolve to meet changing customer needs and to respond to competitive pressures while user populations can grow dramatically and unpredictably. To address these realities, developers are selecting document-oriented databases for schema flexibility, scalability and high performance data storage.
In this session, we will get hands on with Azure’s NoSQL document database service. Azure DocumentDB offers full indexing of JSON documents, SQL query capabilities and multi-document transactions. Learn how to get started with Azure DocumentDB and hear about some of the recent improvements to the service.
Media owners are turning to MongoDB to drive social interaction with their published content. The way customers consume information has changed and passive communication is no longer enough. They want to comment, share and engage with publishers and their community through a range of media types and via multiple channels whenever and wherever they are. There are serious challenges with taking this semi-structured and unstructured data and making it work in a traditional relational database. This webinar looks at how MongoDB’s schemaless design and document orientation gives organisation’s like the Guardian the flexibility to aggregate social content and scale out.
MongoDB provides a concise summary of sharding in MongoDB:
1) Collections can be sharded (partitioned) across multiple servers, with each document assigned to a single shard based on the shard key.
2) Shards are divided into chunks based on the shard key range. Chunk metadata is stored in config servers and cached by mongos processes.
3) A balancer process monitors chunk distribution and migrates chunks between shards to improve balance as data and chunks sizes change over time. This helps distribute load evenly across shards.
Webinar: Best Practices for Getting Started with MongoDBMongoDB
MongoDB adoption continues to grow at a record pace due to the significant enhancements in developer productivity and scalability that the database provides. Occasionally, however, organizations new to the technology make mistakes that limit their ability to leverage the significant advantages MongoDB provides. This webinar will discuss some of the common mistakes made by users when they first start working with MongoDB, how to identify when you've made those mistakes, and how to resolve them.
This tutorial will introduce the features of MongoDB by building a simple location-based application using MongoDB. The tutorial will cover the basics of MongoDB’s document model, query language, map-reduce framework and deployment architecture.
The tutorial will be divided into 5 sections:
Data modeling with MongoDB: documents, collections and databases
Querying your data: simple queries, geospatial queries, and text-searching
Writes and updates: using MongoDB’s atomic update modifiers
Trending and analytics: Using mapreduce and MongoDB’s aggregation framework
Deploying the sample application
Besides the knowledge to start building their own applications with MongoDB, attendees will finish the session with a working application they use to check into locations around Portland from any HTML5 enabled phone!
TUTORIAL PREREQUISITES
Each attendee should have a running version of MongoDB. Preferably the latest unstable release 2.1.x, but any install after 2.0 should be fine. You can dowload MongoDB at http://www.mongodb.org/downloads.
Instructions for installing MongoDB are at http://docs.mongodb.org/manual/installation/.
Additionally we will be building an app in Ruby. Ruby 1.9.3+ is required for this. The current latest version of ruby is 1.9.3-p194.
For windows download the http://rubyinstaller.org/
For OSX download http://unfiniti.com/software/mac/jewelrybox/
For linux most users should know how to for their own distributions.
We will be using the following GEMs and they MUST BE installed ahead of time so you can be ahead of the game and safe in the event that the Internet isn’t accommodating.
bson (1.6.4)
bson_ext (1.6.4)
haml (3.1.4)
mongo (1.6.4)
rack (1.4.1)
rack-protection (1.2.0)
rack shotgun (0.9)
sinatra (1.3.2)
tilt (1.3.3)
Prior ruby experience isn’t required for this. We will NOT be using rails for this app.
NoSQL Analytics: JSON Data Analysis and Acceleration in MongoDB WorldAjay Gupte
In analytics world, when you need to process many millions or billions of documents to generate a single report. Novel techniques have been developed for exploiting modern processor architecture (larger on-chip cache, SIMD processing, compression, vector processing, columnar approach). Now, this technology is available to process your large JSON data. This talk will discuss analysis of JSON data using advanced data warehousing techniques and make it simple and seamless for the application/tool developer.
MongoDB is the leading NoSQL database due to a plenitude of reasons, open source, general purpose, document oriented database supported by a large community and educational platform. It's horizontal scalability features allows this to fit in the operational big data scenarios where the business needs point to realtime analytics and ever-increasing data sets. This talk will focus on the usage of MongoDB for big data operational purposes and why it's ideal to be used in such scenarios. Also integration with other notable big data technology out there like Hadoop and BI tools.
Norberto Leite - Senior Solutions Architect, @MongoDB.
Mongo DB presentation during the Pentaho & Big Data Ecosystem - Live Seminar 2013
The document introduces MongoDB, an open-source document database that provides high performance, high availability, and easy scalability. MongoDB keeps data as JSON-like documents which allows for flexible schemas and is well-suited for applications that work with unstructured or semi-structured data. The document also discusses how MongoDB can be used in conjunction with Hadoop for large-scale data processing and analytics workloads that require more than just a document database.
This presentation reviews Postgres’ unsurpassed NoSQL capabilities, which include a very rich JSON data type, a key-value pair data type, and a SQL/MED-based virtual data integration capability to bridge between Postgres and many other databases. Marc Linster discusses NoSQL syntax, NoSQL performance, and SQL/NoSQL integration and implementation recommendations.
To listen to the recording visit EnterpriseDB.com > Resources > Webcasts > On Demand Webcasts.
If you have any questions, please email sales@enterprisedb.com
NoSQL Now: Postgres - The NoSQL Cake You Can EatDATAVERSITY
The path to creating a single view of your customers or your transactional systems is overflowing with high costs and complexity. Major vendors have built massive, million-dollar systems that are too expensive and too complicated for most. NoSQL-only solutions seem to have promise, but simply do not necessarily have what you need. Learn what Postgres can do for you that NoSQL-only solutions can't.
Using a NoSQL-only solution and dumping gigabytes of data from multiple disparate systems into gigantic documents is complicated. And it forces tough choices—group all data by customer, by transaction, or by policy? You must choose, and this can be a hard process for some organizations. And almost always, organizations later learn they need relationships among the data, which NoSQL-only solutions cannot support.
Postgres eliminates the complexity and the pain of creating a single view of the customer. With recent advances, Postgres can support semi-structured, unstructured and structured data in the same environment, employing relational qualities and ACID compliance.
During this presentation, Marc Linster, SVP Products & Services, will review: ·
How to do more with Postgres
Open source alternative to RDBMS and more...
The NoSQL Conundrum
Why do developers like NoSQL Only solutions?
Problems and fallacies of NoSQL (only)
Data Standards
Data Islands
NoSQL Data Models include data access paths
Not Only SQL - Technology Innovation on a Robust Platform
Document Store
See JSON Examples
360 Degree view of the customer
Data Integration
Postgres eliminates the complexity and the pain of creating a single view of the customer. With recent advances, Postgres can support semi-structured, unstructured and structured data in the same environment, employing relational qualities and ACID compliance.
This presentation reviews:
- How advances in Postgres enable it to match capabilities of NoSQL-only niche solutions·
- How the ETL process in Postgres is simple compared to undoing tables and schemas in order to transfer data to a NoSQL-only system
- How Foreign Data Wrappers – essentially pipelines between Postgres and other databases – work and how they help bridge the gap between disparate systems faster than an ETL process
Visit Enterprisedb.com and go to our Resources section, then Webcasts to listen to the presentation recording.
The document discusses how PostgreSQL can be used as both a relational and NoSQL database, allowing it to meet more development needs than NoSQL databases alone. It outlines PostgreSQL's support for JSON and key-value storage, allowing it to store hierarchical and schemaless data like NoSQL databases while also providing SQL capabilities. This hybrid approach avoids issues like data silos that can occur with only using NoSQL solutions.
NoSQL and Spatial Database Capabilities using PostgreSQLEDB
PostgreSQL is an object-relational database system. NoSQL on the other hand is a non-relational database and is document-oriented. Learn how the PostgreSQL database gives one the flexible options to combine NoSQL workloads with the relational query power by offering JSON data types. With PostgreSQL, new capabilities can be developed and plugged into the database as required.
Attend this webinar to learn:
- The new features and capabilities in PostgreSQL for new workloads, requiring greater flexibility in the data model
- NoSQL with JSON, Hstore and its performance and features for enterprises
- Spatial SQL - advanced features in PostGIS application with PostGIS extension
Application Development & Database Choices: Postgres Support for non Relation...EDB
This talk will cover the advanced features of PostgreSQL that make it the most-loved RDBMS by developers and a great choice for non-relational workloads.
This webinar will explore:
- Global adoption of Postgres
- Document-centric applications
- Geographic Information Systems (GIS)
- Business intelligence
- Central data centers
- Server-side languages
This document discusses using PostgreSQL and its extensions to integrate various data sources. It provides an overview of PostgreSQL's support for JSON, foreign data wrappers (FDWs), and examples of using MongoDB and Cassandra FDWs. Specifically, it covers:
- PostgreSQL's JSON operators and functions for querying and manipulating JSON data
- FDWs allow querying remote data sources like MongoDB, HDFS, and other databases as if they were local tables
- Demos of loading JSON data and using JSON operators, and connecting to MongoDB using the MongoDB FDW
- Examples of companies using MongoDB and Cassandra FDWs with PostgreSQL to integrate different data sources
JSON support in DB2 for z/OS
1. To illustrate JSON storage model in DB2 for z/OS
2. To introduce JSON SQL APIs features and examples
3. To compare JSON and XML support in DB2 for z/OS
Application development with Oracle NoSQL Database 3.0Anuj Sahni
The document introduces table-based data modeling features for Oracle NoSQL Database. It discusses using tables to simplify application data modeling with familiar concepts like tables and data types. Examples show how to model user and email data using tables, including defining the schema using DDL, querying the data using DML, and indexing the tables. The document also provides an example of modeling user and email data from an email client application to illustrate how to approach data modeling.
This document discusses MongoDB and the needs of Rivera Group, an IT services company. It notes that Rivera Group has been using MongoDB since 2012 to store large, multi-dimensional datasets with heavy read/write and audit requirements. The document outlines some of the challenges Rivera Group faces around indexing, aggregation, and flexibility in querying datasets.
Eagle6 is a product that use system artifacts to create a replica model that represents a near real-time view of system architecture. Eagle6 was built to collect system data (log files, application source code, etc.) and to link system behaviors in such a way that the user is able to quickly identify risks associated with unknown or unwanted behavioral events that may result in unknown impacts to seemingly unrelated down-stream systems. This session is designed to present the capabilities of the Eagle6 modeling product and how we are using MongoDB to support near-real-time analysis of large disparate datasets.
Database@Home - Data Driven : Loading, Indexing, and Searching with Text and ...Tammy Bednar
This session will cover loading large JSON datasets into Oracle Database 19c, indexing the content and providing a RESTful search interface - all using Oracle Cloud features.
Postgres has the unique ability to act as a powerful data aggregator or information hub in many IT centers bringing together data from different databases and in different formats.
This presentation reviews Postgres' extensibility, foreign data wrappers, and ability to work with structured relational and unstructured NoSQL-like information such as documents and key-value data.
The Postgres capabilities are unrivaled in enabling a complete view of customers or businesses, analyzing disparate data together, and breaking down data silos within the enterprise.
Target Audience:
This presentation is for DBAs, Data Architects, IT Managers, IT Directors, and IT Strategists who are responsible for supporting Postgres-based applications and deployment with ongoing maintenance of Postgres databases. It is equally suitable for organizations using community PostgreSQL as well as EDB’s Postgres Plus product family.
JSON is an important datatype transporting data between servers and many modern applications. Postgres has been at the forefront of bringing these capabilities into the hands of database users. JSONB data type allows for faster operations within PostgreSQL.
At this webinar we will look at:
- How to use JSON from applications
- How to store it in the database
- How to index JSON data
- Tips and tricks to optimize usage
We then closed with a review of the roadmap for new PostgreSQL features for JSON and JSON standards compliance.
[Given at DAMA WI, Nov 2018] With the increasing prevalence of semi-structured data from IoT devices, web logs, and other sources, data architects and modelers have to learn how to interpret and project data from things like JSON. While the concept of loading data without upfront modeling is appealing to many, ultimately, in order to make sense of the data and use it to drive business value, we have to turn that schema-on-read data into a real schema! That means data modeling! In this session I will walk through both simple and complex JSON documents, decompose them, then turn them into a representative data model using Oracle SQL Developer Data Modeler. I will show you how they might look using both traditional 3NF and data vault styles of modeling. In this session you will:
1. See what a JSON document looks like
2. Understand how to read it
3. Learn how to convert it to a standard data model
Watch this Fast Data Strategy Virtual Summit session with speakers Mano Vajpey, Managing Director, SimplicityBI & John Skier, Director Systems Integration, IBM here: https://goo.gl/Qf2zRW
Today's complex organizations will often have hundreds if not thousands of data repositories, distributed across on-premises stores and now the cloud. For data to become truly democratized, non-specialists and data natives need to be able to easily find and access data without requiring outside help.
Attend this session to discover:
• Why organizations’ need to rethink the way they work with data
• How a data marketplace facilitates a single access point for all of an organization's data assets
• The role of data virtualization in enabling a data marketplace
MongoDB Schema Design: Practical Applications and ImplicationsMongoDB
Presented by Austin Zellner, Solutions Architect, MongoDB
Schema design is as much art as it is science, but it is central to understanding how to get the most out of MongoDB. Attendees will walk away with an understanding of how to approach schema design, what influences it, and the science behind the art. After this session, attendees will be ready to design new schemas, as well as re-evaluate existing schemas with a new mental model.
MySQL como Document Store PHP Conference 2017MySQL Brasil
Conheça uma nova forma schemaless de usar o MySQL e ganhe produtividade e flexibilidade ao trabalhar diretamente com documentos JSON, chave-valor ou híbrido NoSQL e SQL.
The document discusses plans for Java EE 8 based on feedback from the Java EE community. Key areas of focus for Java EE 8 include enhancements to support HTML5/web standards like JSON binding, processing and server-sent events. The document outlines specific APIs and features being considered for these areas based on industry trends and priorities identified in a community survey. Additional themes for Java EE 8 are improved ease of development, alignment with CDI and infrastructure for cloud deployments.
Integration intervention: Get your apps and data up to speedKenneth Peeples
SOA has been the defacto methodology for enterprise application and process integration, because loosely coupled components and composite applications are more agile and efficient. The perfect solution? Not quite.
The data’s always been the problem. The most efficient and agile applications and services can be dragged down by the point-to-point data connections of a traditional data integration stack. Virtualized data services can eliminate the friction and get your applications up to speed.
In this webinar we'll show you how to (replay at http://www.redhat.com/en/about/events/integration-intervention-get-your-apps-and-data-speed):
-Quickly and easily create a virtual data services layer to plug data into your SOA infrastructure for an agile and efficient solution
-Derive more business value from your services.
Similar to Do More with Postgres- NoSQL Applications for the Enterprise (20)
Cloud Migration Paths: Kubernetes, IaaS, or DBaaSEDB
Moving to the cloud is hard, and moving Postgres databases to the cloud is even harder. Public cloud or private cloud? Infrastructure as a Service (IaaS), or Platform as a Service (PaaS)? Kubernetes for the application, or for the database and the application? This talk will juxtapose self-managed Kubernetes and container-based database solutions, Postgres deployments on IaaS, and Postgres DBaaS solutions of which EDB’s DBaaS BigAnimal is the latest example.
Die 10 besten PostgreSQL-Replikationsstrategien für Ihr UnternehmenEDB
Dieses Webinar hilft Ihnen, die Unterschiede zwischen den verschiedenen Replikationsansätzen zu verstehen, die Anforderungen der jeweiligen Strategie zu erkennen und sich über die Möglichkeiten klar zu werden, was mit jeder einzelnen zu erreichen ist. Damit werden Sie hoffentlich eher in der Lage sein, herauszufinden, welche PostgreSQL-Replikationsarten Sie wirklich für Ihr System benötigen.
- Wie physische und logische Replikation in PostgreSQL funktionieren
- Unterschiede zwischen synchroner und asynchroner Replikation
- Vorteile, Nachteile und Herausforderungen bei der Multi-Master-Replikation
- Welche Replikationsstrategie für unterschiedliche Use-Cases besser geeignet ist
Referent:
Borys Neselovskyi, Regional Sales Engineer DACH, EDB
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For more #webinars, visit http://bit.ly/EDB-Webinars
Download free #PostgreSQL whitepapers: http://bit.ly/EDB-Whitepapers
Read our #Postgres Blog http://bit.ly/EDB-Blogs
Follow us on Facebook at http://bit.ly/EDB-FB
Follow us on Twitter at http://bit.ly/EDB-Twitter
Follow us on LinkedIn at http://bit.ly/EDB-LinkedIn
Reach us via email at marketing@enterprisedb.com
Cuando busca alternativas a Oracle en la nube, hacer el cambio puede parecer un trabajo duro. Entendemos que la migración involucra más que solo la base de datos. La compatibilidad es un punto clave, especialmente cuando se consideran los recursos que posiblemente ya haya invertido en Oracle, como por ejemplo el código de aplicación específico de Oracle.Este seminario web explorará las opciones y las principales consideraciones al pasar de las bases de datos de Oracle a la nube.
- Revisión detallada de las ofertas de bases de datos disponibles en la nube
- Factores críticos que se deben considerar considerar para elegir la oferta en la nube más adecuada
- Cómo la experiencia de EDB con PostgreSQL puede ayudarlo en su decisión
- Demostración de BigAnimal de EDB
Présentateur:
Sergio Romera, Senior Sales Engineer EMEA, EDB
------------------------------------------------------------
For more #webinars, visit http://bit.ly/EDB-Webinars
Download free #PostgreSQL whitepapers: http://bit.ly/EDB-Whitepapers
Read our #Postgres Blog http://bit.ly/EDB-Blogs
Follow us on Facebook at http://bit.ly/EDB-FB
Follow us on Twitter at http://bit.ly/EDB-Twitter
Follow us on LinkedIn at http://bit.ly/EDB-LinkedIn
Reach us via email at marketing@enterprisedb.com
This document provides an overview and demonstration of EnterpriseDB's Failover Manager (EFM). It begins with an overview of EFM's capabilities in ensuring high availability and minimizing downtime during database upgrades or maintenance. It then covers installation and configuration prerequisites, supported platforms, and the EFM architecture involving a primary, standby, and witness database nodes. The remainder demonstrates switchover and failover functionality through a live demo in a replication environment using CentOS 7.7 and EnterpriseDB PostgreSQL Advanced Server 13.
Database come PostgreSQL non possono girare su Kubernetes. Questo è il ritornello che sentiamo continuamente, ma al tempo stesso la motivazione per noi di EDB di abbattere questo muro, una volta per tutte.
In questo webinar parleremo della nostra avventura finora per portare PostgreSQL su Kubernetes. Scopri perché crediamo che fare benchmark di storage e del database prima di andare in produzione porti a una più sana e longeva vita di un DBMS, anche su Kubernetes.
Condivideremo il nostro processo, i risultati fin qui ottenuti e sveleremo i nostri piani per il futuro con Cloud Native PostgreSQL.
Las Variaciones de la Replicación de PostgreSQLEDB
Replicación física, replicación lógica, síncrona, asíncrona, multi-maestro, escalabilidad horizontal, etc. Son muchos los términos asociados con la replicación de bases de datos. En esta charla revisaremos los conceptos fundamentales detrás de cada variación de la replicación de PostgreSQL, y en qué casos conviene usar una o la otra. La presentación incluye una parte práctica con demostraciones aunque no será un tutorial sobre como configurar un cluster. El enfoque está en entender cada variación para elegir la mejor dependiendo del caso de uso.
Cosas que aprenderán:
- Cómo funciona la replicación física en PostgreSQL
- Cómo funciona la replicación lógica en PostgreSQL
- Diferencias entre replicación síncrona y asíncrona
- Qué es replicación multi-maestro
"Why use PgBouncer? It’s a lightweight, easy to configure connection pooler and it does one job well. As you’d expect from a talk on connection pooling, we’ll give a brief summary of connection pooling and why it increases efficiency. We’ll look at when not to use connection pooling, and we’ll demonstrate how to configure PgBouncer and how it works. But. Did you know you can also do this? 1. Scaling PgBouncer PgBouncer is single threaded which means a single instance of PgBouncer isn’t going to do you much good on a multi-threaded and/or multi-CPU machine. We’ll show you how to add more PgBouncer instances so you can use more than one thread for easy scaling. 2. Read-write / read only routing Using different pgBouncer databases you can route read-write traffic to the primary database and route read-only traffic to a number of standby databases. 3. Load balancing When we use multiple PgBouncer instances, load balancing comes for free. Load balancing can be directed to different standbys, and weighted according to ratios of load. 4. Silent failover You can perform silent failover during promotion of a new primary (assuming you have a VIP/DNS etc that always points to the primary). 5. And even: DoS prevention and protection from “badly behaved” applications! By using distinct port numbers you can provide database connections which deal with sudden bursts of incoming traffic in very different ways, which can help prevent the database from becoming swamped during high activity periods. You should leave the presentation wondering if there is anything PgBouncer can’t do."
In this talk I'll discuss how we can combine the power of PostgreSQL with TensorFlow to perform data analysis. By using the pl/python3 procedural language we can integrate machine learning libraries such as TensorFlow with PostgreSQL, opening the door for powerful data analytics combining SQL with AI. Typical use-cases might involve regression analysis to find relationships in an existing dataset and to predict results based on new inputs, or to analyse time series data and extrapolate future data taking into account general trends and seasonal variability whilst ignoring noise. Python is an ideal language for building custom systems to do this kind of work as it gives us access to a rich ecosystem of libraries such as Pandas and Numpy, in addition to TensorFlow itself.
Practical Partitioning in Production with PostgresEDB
Has your table become too large to handle? Have you thought about chopping it up into smaller pieces that are easier to query and maintain? What if it's in constant use? An introduction to the problems that can arise and how PostgreSQL's partitioning features can help, followed by a real-world scenario of partitioning an existing huge table on a live system. We will be looking at the problems caused by having very large tables in your database and how declarative table partitioning in Postgres can help. Also, how to perform dimensioning before but also after creating huge tables, partitioning key selection, the importance of upgrading to get the latest Postgres features and finally we will dive into a real-world scenario of having to partition an existing huge table in use on a production system.
There have been plenty of “explaining EXPLAIN” type talks over the years, which provide a great introduction to it. They often also cover how to identify a few of the more common issues through it. EXPLAIN is a deep topic though, and to do a good introduction talk, you have to skip over a lot of the tricky bits. As such, this talk will not be a good introduction to EXPLAIN, but instead a deeper dive into some of the things most don’t cover. The idea is to start with some of the more complex and unintuitive calculations needed to work out the relationships between operations, rows, threads, loops, timings, buffers, CTEs and subplans. Most popular tools handle at least several of these well, but there are cases where they don’t that are worth being conscious of and alert to. For example, we’ll have a look at whether certain numbers are averaged per-loop or per-thread, or both. We’ll also cover a resulting rounding issue or two to be on the lookout for. Finally, some per-operation timing quirks are worth looking out for where CTEs and subqueries are concerned, for example CTEs that are referenced more than once. As time allows, we can also look at a few rarer issues that can be spotted via EXPLAIN, as well as a few more gotchas that we’ve picked up along the way. This includes things like spotting when the query is JIT, planning, or trigger time dominated, spotting the signs of table and index bloat, issues like lossy bitmap scans or index-only scans fetching from the heap, as well as some things to be aware of when using auto_explain.
This document provides an overview of using PostgreSQL for IoT applications. Chris Ellis discusses why PostgreSQL is a good fit for IoT due to its flexibility and extensibility. He describes various ways of storing, loading, and processing IoT time series and sensor data in PostgreSQL, including partitioning, batch loading, and window functions. The document also briefly mentions the TimescaleDB extension for additional time series functionality.
The document describes a migration from an Oracle database topology to a PostgreSQL database topology at ACI. It discusses the starting Oracle topology with issues around operational complexity and non-ACID compliance. It then describes the target PostgreSQL topology with improved performance, availability and lower costs. The document outlines decisions around tools, extensions, code changes and testing approaches needed for the migration. It also discusses options for migrating the data and cutting over to the new PostgreSQL environment.
The document provides an introduction to using the psql command line tool for interacting with PostgreSQL databases. It explains how to connect to a database, perform basic queries, explain query plans, and get information about tables, schemas, and users.
EDB 13 - New Enhancements for Security and Usability - APJEDB
Database security is always of paramount importance to all organizations. In this webinar, we will explore the security, usability, and portability updates of the latest version of the EDB database server and tools.
Join us in this webinar to learn:
- The new security features such as SCRAM and the encryption of database passwords and traffic between Failover Manager agents
- Usability updates that automate partitioning, verify backup integrity, and streamline the management of failover and backups
- Portability improvements that simplify running PostgreSQL across on-premise and cloud environments
Dans ce webinar, nous allons parler des différences entre une sauvegarde physique et une sauvegarde logique. Nous allons lister les avantages et inconvénients, les principales considérations et les outils disponibles pour les deux méthodes.
- Perte de données
- Exports logiques
- Standbys
- WALs et Recovery
- Snapshots VM/Disques
- Sauvegardes physique
- Conclusion
Vieni a scoprire Cloud Native PostgreSQL (CNP), l’operatore per Kubernetes, direttamente da coloro che lo hanno ideato e lo sviluppano in EDB.
CNP facilita l’integrazione di database PostgreSQL con le tue applicazioni all’interno di cluster Kubernetes e OpenShift Container Platform di RedHat, grazie alla sua gestione automatica dell’architettura primario/standby che include: self-healing, failover, switchover, rolling update, backup, ecc.
Durante il webinar affronteremo i seguenti punti:
- DevOps e Cloud Native
- Introduzione a Cloud Native PostgreSQL
- Architetture
- Caratteristiche principali
- Esempi di uso e configurazione
- Kubernetes, Storage e Postgres
- Demo
- Conclusioni
New enhancements for security and usability in EDB 13EDB
EDB 13 enhances our flagship database server and tools. This webinar will explore its security, usability, and portability updates. Join us to learn how EDB 13 can help you improve your PostgreSQL productivity and data protection.
Webinar highlights include:
- New security features such as SCRAM and the encryption of database passwords and traffic between Failover Manager agents
- Usability updates that automate partitioning, verify backup integrity and streamline the management of failover and backups
- Portability improvements that simplify running PostgreSQL across on-premise and cloud environments
The webinar will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data.
Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
- Best practices for authentication (trust, certificate, MD5, Scram, etc).
- Advanced approaches, such as password profiles.
- Deep dive of authorization and data access control for roles, database objects (tables, etc), view usage, row-level security, and data redaction.
- Auditing, encryption, and SQL injection attack prevention.
Note: this session is delivered in German
Speaker:
Borys Neselovskyi, Sales Engineer, EDB
EDB Cloud Native Postgres includes database container images and a Kubernetes Operator that manage the lifecycle of a database from deployment to operations. This Kubernetes Operator for Postgres is written by EDB entirely from scratch in the Go language and relies exclusively on the Kubernetes API.
Attend this webinar to learn about:
- DevOps & Cloud Native
- Overview of Cloud Native Postgres
- Storage for Postgres workloads in Kubernetes
- Using Cloud Native Postgres
- Demo
The webinar will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data.
Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
- Best practices for authentication (trust, certificate, MD5, Scram, etc).
- Advanced approaches, such as password profiles.
- Deep dive of authorization and data access control for roles, database objects (tables, etc), view usage, row-level security, and data redaction.
- Auditing, encryption, and SQL injection attack prevention.
Note: this session is delivered in French
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
This is the roadmap for content of the meeting
Adjust as necessary based on previous discussions on objectives and areas of interest
Goal is to set expectations for content to be discussed
Agree on specific meeting objectives/outcomes up front
Inquire about any specific areas of interest or current needs that should be emphasized
Introduction to EDB
EDB provides enterprises and government agencies with the commercial support and reliability needed to take full advantage of open-source Postgres innovation and cost benefits:
24/7 Support
Enterprise-class features & tools
Packaged and professional services
Wide array of classroom and on-demand training
Clear visibility & influence over product road-map
EDB gives you the responsiveness & dependability you need to be successful
Overview of EDB products & Services
NOTE: THIS SLIDE HAS BUILT-IN “JUMPING” SO YOU CAN CLICK ON ANY ICON TO DRILL DOWN THEN RETURN TO THE OVERVIEW; here’s how:
Click on each icon (DBs and services) to drill down to details
Once on detail page, click on the icon to move directly to the next icon detail, or
Click on the area outside of the drill down detail to return back to the main product & services overview
Main message: EDB is the BEST source for all your Postgres needs:
EDB is a database internals product development company
EDB creates add-on features, tools and cloud capabilities designed for enterprise-class workloads
EDB’s deep technical expertise makes it your best source for support and professional services
Sample script:
“Just as you’d expect from any enterprise software company, EDB provides various products and services to ensure our customers make the most out of their Postgres deployments. From our standard edition which includes support for the open source PostgreSQL to PPAS and PPCD, we have the right database for your application. We back that up with global follow the sun support, packaged services and training along with RDBA services.
Many of customers run PostgreSQL and come to us for support and to take advantage of our add-on functionality, such as PEM and xDB replication server. For lots of workloads this is a fine solution.
The majority of our customers do run PPAS, though. The combination of its low cost--$6,900 per year per socket, along with a ton of additional features and functionality above the Standard Edition, it’s a great fit for workloads with lots of concurrent users and lots of transactions.
Of course, PPCD gives customers the ability to run either PostgreSQL or PPAS, but in a cloud environment.”
Bruce
Marc Linster
Emergency Management System: Rapid integration of heterogeneous data sources for new analysis platform
- High variability among data sources required high schema flexibility
MOOC:
- Massive read sclability
- Content integration from a variety of sources
- Low latency at peak volumes
Patient data and prescription records
- Distributed key-value store reduced complexity of integration and management overhead
Online Gambling
- Key value store simplified development (up to 75% acceleration)
- Efficient write sclability
Online Marketing Firm
- massive time series storage facilitated by table style DBMS
- data center replication
Social Marketing Analytics
- Massive amounts of data from social media systems
- Map-reduce analytical approaches
Product Manufacturing Master Data Management
- Network dependencies between product lines
Drug Discovery
- Drug Analysis
Bruce
Bruce
Note:
1. JSON generally ignores any whitespace around or between syntactic elements (values and punctuation, but not within a string value).
2. JSON only recognizes four specific whitespace characters:
i. the space
ii. horizontal tab,
iii. line feed, and carriage return.
3. JSON does not provide or allow any sort of comment syntax.