The document discusses Couchbase's data structures and sub-document APIs. It provides an overview of the features and benefits of Couchbase's data structures API, which allows simplified access to JSON documents without touching the whole document. It also discusses Couchbase's sub-document API, which enables efficient access to parts of JSON documents without transferring the entire document. The document covers considerations for data modeling with Couchbase, including the benefits of different approaches to structuring data in JSON documents.
The document discusses different types of NoSQL databases including key-value stores like Memcached and Redis, document databases like Couchbase and MongoDB, column-oriented databases like Cassandra, and graph databases like Neo4j. It explains the basic data models and architectures of each type of NoSQL database. NoSQL databases provide more flexible schemas and better horizontal scalability than traditional relational databases.
This document provides an introduction and overview of Couchbase Server, a NoSQL document database. It describes Couchbase Server as the leading open source project focused on distributed database technology. It outlines key features such as easy scalability, always-on availability, flexible data modeling using JSON documents, and core features including clustering, replication, indexing and querying. The document also provides examples of basic write, read and update operations on a single node and cluster, adding nodes, handling node failures, indexing and querying capabilities, and cross data center replication.
The document provides an overview of Couchbase, a distributed document database. It describes Couchbase as a leading NoSQL database company that provides a more flexible, higher performance and scalable alternative to relational databases. Couchbase uses a document-oriented data model and scales out easily by adding more commodity servers. It has over 5,000 paid production deployments worldwide with customers in internet companies and enterprises.
This document introduces Couchbase 4.5 and Couchbase Mobile 1.2 and discusses several use cases for using Couchbase as a NoSQL database solution. It summarizes five common use cases: 1) high-availability caching to speed up database operations, 2) using Couchbase as a session store, 3) creating a globally distributed user profile store, 4) aggregating data from various sources, and 5) storing and accessing content and metadata.
Building Google-in-a-box: using Apache SolrCloud and Bigtop to index your big...rhatr
You’ve got your Hadoop cluster, you’ve got your petabytes of unstructured data, you run mapreduce jobs and SQL-on-Hadoop queries. Something is still missing though. After all, we are not expected to enter SQL queries while looking for information on the web. Altavista and Google solved it for us ages ago. Why are we still requiring SQL or Java certification from our enterprise bigdata users? In this talk, we will look into how integration of SolrCloud into Apache Bigtop is now enabling building bigdata indexing solutions and ingest pipelines. We will dive into the details of integrating full-text search into the lifecycle of your bigdata management applications and exposing the power of Google-in-a-box to all enterprise users, not just a chosen few data scientists.
This document discusses using big data tools to build a fraud detection system. It outlines using Azure infrastructure to set up a Hadoop cluster with HDFS, HBase, Kafka and Spark. Mock transaction data will be generated and sent to Kafka. Spark jobs will process the data in batches, identifying potentially fraudulent transactions and writing them to an HBase table. The data will be visualized using Zeppelin notebooks querying Phoenix SQL on HBase. This will allow analysts to further investigate potential fraud patterns in near real-time.
Solr cloud the 'search first' nosql database extended deep divelucenerevolution
Presented by Mark Miller, Software Engineer, Cloudera
As the NoSQL ecosystem looks to integrate great search, great search is naturally beginning to expose many NoSQL features. Will these Goliath's collide? Or will they remain specialized while intermingling – two sides of the same coin.
Come learn about where SolrCloud fits into the NoSQL landscape. What can it do? What will it do? And how will the big data, NoSQL, Search ecosystem evolve. If you are interested in Big Data, NoSQL, distributed systems, CAP theorem and other hype filled terms, than this talk may be for you.
Before joining Couchbase Phil has been a consultant on many different node.js and NoSQL projects working with many different languages and databases. By helping clients solve problems regarding scalability as well building completely new APIs he gained a broad knowledge of the available platforms and their tradeoffs in the big and small. He's a Developer Evangelist for Couchbase where he works to educate developers on the different parts of using a NoSQL database from mobile to big iron servers.
The document discusses different types of NoSQL databases including key-value stores like Memcached and Redis, document databases like Couchbase and MongoDB, column-oriented databases like Cassandra, and graph databases like Neo4j. It explains the basic data models and architectures of each type of NoSQL database. NoSQL databases provide more flexible schemas and better horizontal scalability than traditional relational databases.
This document provides an introduction and overview of Couchbase Server, a NoSQL document database. It describes Couchbase Server as the leading open source project focused on distributed database technology. It outlines key features such as easy scalability, always-on availability, flexible data modeling using JSON documents, and core features including clustering, replication, indexing and querying. The document also provides examples of basic write, read and update operations on a single node and cluster, adding nodes, handling node failures, indexing and querying capabilities, and cross data center replication.
The document provides an overview of Couchbase, a distributed document database. It describes Couchbase as a leading NoSQL database company that provides a more flexible, higher performance and scalable alternative to relational databases. Couchbase uses a document-oriented data model and scales out easily by adding more commodity servers. It has over 5,000 paid production deployments worldwide with customers in internet companies and enterprises.
This document introduces Couchbase 4.5 and Couchbase Mobile 1.2 and discusses several use cases for using Couchbase as a NoSQL database solution. It summarizes five common use cases: 1) high-availability caching to speed up database operations, 2) using Couchbase as a session store, 3) creating a globally distributed user profile store, 4) aggregating data from various sources, and 5) storing and accessing content and metadata.
Building Google-in-a-box: using Apache SolrCloud and Bigtop to index your big...rhatr
You’ve got your Hadoop cluster, you’ve got your petabytes of unstructured data, you run mapreduce jobs and SQL-on-Hadoop queries. Something is still missing though. After all, we are not expected to enter SQL queries while looking for information on the web. Altavista and Google solved it for us ages ago. Why are we still requiring SQL or Java certification from our enterprise bigdata users? In this talk, we will look into how integration of SolrCloud into Apache Bigtop is now enabling building bigdata indexing solutions and ingest pipelines. We will dive into the details of integrating full-text search into the lifecycle of your bigdata management applications and exposing the power of Google-in-a-box to all enterprise users, not just a chosen few data scientists.
This document discusses using big data tools to build a fraud detection system. It outlines using Azure infrastructure to set up a Hadoop cluster with HDFS, HBase, Kafka and Spark. Mock transaction data will be generated and sent to Kafka. Spark jobs will process the data in batches, identifying potentially fraudulent transactions and writing them to an HBase table. The data will be visualized using Zeppelin notebooks querying Phoenix SQL on HBase. This will allow analysts to further investigate potential fraud patterns in near real-time.
Solr cloud the 'search first' nosql database extended deep divelucenerevolution
Presented by Mark Miller, Software Engineer, Cloudera
As the NoSQL ecosystem looks to integrate great search, great search is naturally beginning to expose many NoSQL features. Will these Goliath's collide? Or will they remain specialized while intermingling – two sides of the same coin.
Come learn about where SolrCloud fits into the NoSQL landscape. What can it do? What will it do? And how will the big data, NoSQL, Search ecosystem evolve. If you are interested in Big Data, NoSQL, distributed systems, CAP theorem and other hype filled terms, than this talk may be for you.
Before joining Couchbase Phil has been a consultant on many different node.js and NoSQL projects working with many different languages and databases. By helping clients solve problems regarding scalability as well building completely new APIs he gained a broad knowledge of the available platforms and their tradeoffs in the big and small. He's a Developer Evangelist for Couchbase where he works to educate developers on the different parts of using a NoSQL database from mobile to big iron servers.
No SQL, No Problem: Use Azure DocumentDBKen Cenerelli
Introduction to Microsoft Azure DocumentDB. The slides have sections on Overview, Resource Model, Data Modeling, Performance, Development, Pricing and DocumentDB resources.
This talk was given at the following locales:
- DevTeach Montreal (July 6, 2016)
Hear Ryan Millay, IBM Cloudant software development manager, discuss what you need to consider when moving from world of relational databases to a NoSQL document store.
You'll learn about the key differences between relational databases and JSON document stores like Cloudant, as well as how to dodge the pitfalls of migrating from a relational database to NoSQL.
The document provides an overview of different NoSQL database types, including key-value stores, document databases, column-oriented databases, graph databases, and caches. It discusses examples of databases for each type and common use cases. The document also covers querying graph databases, polyglot persistence using multiple database types, and concludes with when each database type is best suited and when not to use a NoSQL database.
The document provides an agenda and overview for an Icinga project presentation. It discusses the structure of the Icinga project including separate teams for the core, API, web interface, and documentation. It provides updates on the status of each component, including migrations to new databases and programming languages. Live demos of the monitoring interface and roadmaps are also outlined.
The document summarizes the history and current state of the MySQL database server ecosystem. It discusses the origins and development of MySQL, MariaDB, Percona Server, and other related projects. It also describes some of the key features and innovations in recent versions of these database servers. The ecosystem is very active with contributions from many organizations and the future remains promising with ongoing work.
Things Every Oracle DBA Needs to Know about the Hadoop EcosystemZohar Elkayam
Session from BGOUG I presented in June, 2016
Big data is one of the biggest buzzword in today's market. Terms like Hadoop, HDFS, YARN, Sqoop, and non-structured data has been scaring DBA's since 2010 - but where does the DBA team really fit in?
In this session, we will discuss everything database administrators and database developers needs to know about big data. We will demystify the Hadoop ecosystem and explore the different components. We will learn how HDFS and MapReduce are changing the data world, and where traditional databases fits into the grand scheme of things. We will also talk about why DBAs are the perfect candidates to transition into Big Data and Hadoop professionals and experts.
The document discusses three open source software projects used by the Internet Archive (IA) for web archiving: Heritrix for crawling, Wayback for browsing and searching by URL, and NutchWAX for full-text search. It provides an overview of each project including their origins and evolutions over time, with improvements to functionality, performance, and features. The goals for future development are also mentioned, focusing on continued enhancements to better support the large-scale web archiving needs of the IA and its partners.
The DSpace infrastructure for logging page-views and downloads has been limited to aggregations on communities, collections and items. While this already provides a wealth of aggregated information that is impossible to retrieve using Google Analytics, it still does not assist a repository manager in addressing questions such as:
“How many downloads did Professor X get through Google Scholar last month?”
Because authors are represented as metadata on items, tackling this challenge effectively means opening the potential to aggregate pageview and download statistics on any metadata field in the repository.
By the time of the conference, functionality that addresses this need will be available as part of @mire’s Content and Usage analysis module. The metadata based usage statistics were realized in co-development with the World Bank.
Presentation created by Lieven Droogmans, Art Lowel and Ignace Deroost.
Presented at Open Repositories 2015 by Ignace Deroost.
This document provides an introduction to Cloudant, which is a fully managed NoSQL database as a service (DBaaS) that provides a scalable and flexible data layer for web and mobile applications. The presentation discusses NoSQL databases and why they are useful, describes Cloudant's features such as document storage, querying, indexing and its global data presence. It also provides examples of how companies like FitnessKeeper and Fidelity Investments use Cloudant to solve data scaling and management challenges. The document concludes by outlining next steps for signing up and exploring Cloudant.
Princeton University Press to Drupal 8: Migration case study by Evolving Webdergachev
We present a case study of our work-in-progress of migrating press.princeton.edu to Drupal 8. In the first phase, we have created a migration script to move over 11,000 published works and 40,000 related entities published over many decades into Drupal, and a content audit of tens of thousands of static HTML pages that has accumulated over the years. We will describe the technical and business motivations for the project, provide a technical overview of the Drupal migration, and of the the process challenges in dealing with this volume of content. Finally, we will describe the next set of challenges as we work with their Press to clarify their branding goals and redo the visual identity.
For video, see https://www.youtube.com/watch?v=52gAQDXS8Zc&feature=youtu.be
Cloudant Overview Bluemix Meetup from Lisa NeddamRomeo Kienzler
Cloudant is a fully-managed NoSQL distributed data layer service based on a JSON document store that provides high availability, scalability, simplicity and performance. It uses a flexible schema and scales massively while always being available. Cloudant is an operational data store and NoSQL document database with a simple HTTP API that is fully integrated with mobile devices, big data, cloud and delivery. It provides replication, sync, real-time analytics using MapReduce, full-text search and geospatial capabilities.
Things Every Oracle DBA Needs To Know About The Hadoop EcosystemZohar Elkayam
This is a presentation which was presented in multiple forums (in one way or the other). This is a short introduction for Oracle personal (DBAs and DB Developers) for Big Data and the Hadoop Ecosystem.
In the agenda:
• What is the Big Data challenge?
• A Big Data Solution: Apache Hadoop
• HDFS
• MapReduce and YARN
• Hadoop Ecosystem: HBase, Sqoop, Hive, Pig and other tools
• Another Big Data Solution: Apache Spark
• Where does the DBA fits in?
This presentation was presented in DOAG 2016, HROUG 2016, BGOUG 2016, ILOUG Tech Days 2016 and other small private sessions (Israel Technology Police leaders, CIO forum, Amdocs, and others).
The document provides an overview of Couchbase's NoSQL document database capabilities for interactive applications. It discusses Couchbase's leadership in the NoSQL market, common use cases where NoSQL is a good fit like mobile apps and caching, and how Couchbase allows for JSON data everywhere from devices to servers. Relational databases are compared to Couchbase, with Couchbase able to scale out more easily to very large datasets and workloads.
Sql Server Tuning for SharePoint : what every consultant must know (Office 36...serge luca
This document discusses tuning SQL Server for SharePoint. It covers operating system settings like NTFS allocation units and IOPS requirements. SQL Server configuration topics include using a dedicated SQL instance, database recovery models, tempdb settings, and file placement. Database concepts explained include SharePoint database types and SQL Server integration. SQL Server optimization techniques like resource governor and performance counters are also outlined. High availability and disaster recovery options like Always On Availability Groups are then covered.
This document provides an overview and agenda for a presentation on business intelligence and big data technologies. The presentation covers tools such as Excel, PowerPivot, Power View, Reporting Services, PerformancePoint, and HDInsight for working with data from sources like SQL Server, Oracle, DB2, and Hadoop. It discusses self-service BI capabilities and how these tools work with the Microsoft BI stack and platform.
This document provides tips and best practices for configuring ArcGIS Open Data services and sites. Key recommendations include:
- Preparing data by adding attribute aliases and hiding unnecessary fields.
- Configuring services with a max record count under 5,000, enabling WMS/WFS/WCS where applicable, and organizing datasets into multiple services with no more than 20 datasets each.
- Structuring the ArcGIS Online organization with appropriate user roles, staging groups, and registering individual layers to control metadata.
- Customizing the site design through header CSS, placing categories and groups on homepage, and adding contact information.
Maria db 10 and the mariadb foundation(colin)kayokogoto
This document provides an overview of MariaDB 10 and the MariaDB Foundation. It discusses the history and development of MariaDB, including key features added in versions 5.1 through 10.0 such as new storage engines, performance improvements, and features backported from MySQL. It outlines the goals of MariaDB to be compatible with MySQL while adding new features, and describes the community-led development model. The roadmap aims to have MariaDB be a drop-in replacement for MySQL 5.6 by releasing version 10.1.
Slides: NoSQL Data Modeling Using JSON Documents – A Practical ApproachDATAVERSITY
After three decades of relational data modeling, everyone’s pretty comfortable with schemas, tables, and entity-relationships. As more and more Global 2000 companies choose NoSQL databases to power their Digital Economy applications, they need to think about how to best model their data. How do they move from a constrained, table-driven model to an agile, flexible data model based on JSON documents?
This webinar is intended for architects and application developers who want to learn about new JSON document data modeling approaches, techniques, and best practices. This webinar will show you how to get started building a JSON document data model, how to migrate a table-based data model to JSON documents, and how to optimize your design to enable fast query performance.
This webinar will provide practical, experience-based advice and best practices for modeling JSON documents, including:
- When to embed or not embed objects in your JSON document
- Data modeling using a practical data access pattern approach
- Indexing your JSON documents
- Querying your data using N1QL (SQL for JSON)
This document introduces Couchbase, an open-source distributed operational database. It discusses how Couchbase provides scalability and high performance through its architecture which allows independent scaling of data, querying, and indexing workloads. It also highlights Couchbase capabilities like JSON document storage, N1QL querying, asynchronous writes, SDKs, full-text search, and cross data center replication. Examples of Couchbase uses at large companies like eBay are also presented.
No SQL, No Problem: Use Azure DocumentDBKen Cenerelli
Introduction to Microsoft Azure DocumentDB. The slides have sections on Overview, Resource Model, Data Modeling, Performance, Development, Pricing and DocumentDB resources.
This talk was given at the following locales:
- DevTeach Montreal (July 6, 2016)
Hear Ryan Millay, IBM Cloudant software development manager, discuss what you need to consider when moving from world of relational databases to a NoSQL document store.
You'll learn about the key differences between relational databases and JSON document stores like Cloudant, as well as how to dodge the pitfalls of migrating from a relational database to NoSQL.
The document provides an overview of different NoSQL database types, including key-value stores, document databases, column-oriented databases, graph databases, and caches. It discusses examples of databases for each type and common use cases. The document also covers querying graph databases, polyglot persistence using multiple database types, and concludes with when each database type is best suited and when not to use a NoSQL database.
The document provides an agenda and overview for an Icinga project presentation. It discusses the structure of the Icinga project including separate teams for the core, API, web interface, and documentation. It provides updates on the status of each component, including migrations to new databases and programming languages. Live demos of the monitoring interface and roadmaps are also outlined.
The document summarizes the history and current state of the MySQL database server ecosystem. It discusses the origins and development of MySQL, MariaDB, Percona Server, and other related projects. It also describes some of the key features and innovations in recent versions of these database servers. The ecosystem is very active with contributions from many organizations and the future remains promising with ongoing work.
Things Every Oracle DBA Needs to Know about the Hadoop EcosystemZohar Elkayam
Session from BGOUG I presented in June, 2016
Big data is one of the biggest buzzword in today's market. Terms like Hadoop, HDFS, YARN, Sqoop, and non-structured data has been scaring DBA's since 2010 - but where does the DBA team really fit in?
In this session, we will discuss everything database administrators and database developers needs to know about big data. We will demystify the Hadoop ecosystem and explore the different components. We will learn how HDFS and MapReduce are changing the data world, and where traditional databases fits into the grand scheme of things. We will also talk about why DBAs are the perfect candidates to transition into Big Data and Hadoop professionals and experts.
The document discusses three open source software projects used by the Internet Archive (IA) for web archiving: Heritrix for crawling, Wayback for browsing and searching by URL, and NutchWAX for full-text search. It provides an overview of each project including their origins and evolutions over time, with improvements to functionality, performance, and features. The goals for future development are also mentioned, focusing on continued enhancements to better support the large-scale web archiving needs of the IA and its partners.
The DSpace infrastructure for logging page-views and downloads has been limited to aggregations on communities, collections and items. While this already provides a wealth of aggregated information that is impossible to retrieve using Google Analytics, it still does not assist a repository manager in addressing questions such as:
“How many downloads did Professor X get through Google Scholar last month?”
Because authors are represented as metadata on items, tackling this challenge effectively means opening the potential to aggregate pageview and download statistics on any metadata field in the repository.
By the time of the conference, functionality that addresses this need will be available as part of @mire’s Content and Usage analysis module. The metadata based usage statistics were realized in co-development with the World Bank.
Presentation created by Lieven Droogmans, Art Lowel and Ignace Deroost.
Presented at Open Repositories 2015 by Ignace Deroost.
This document provides an introduction to Cloudant, which is a fully managed NoSQL database as a service (DBaaS) that provides a scalable and flexible data layer for web and mobile applications. The presentation discusses NoSQL databases and why they are useful, describes Cloudant's features such as document storage, querying, indexing and its global data presence. It also provides examples of how companies like FitnessKeeper and Fidelity Investments use Cloudant to solve data scaling and management challenges. The document concludes by outlining next steps for signing up and exploring Cloudant.
Princeton University Press to Drupal 8: Migration case study by Evolving Webdergachev
We present a case study of our work-in-progress of migrating press.princeton.edu to Drupal 8. In the first phase, we have created a migration script to move over 11,000 published works and 40,000 related entities published over many decades into Drupal, and a content audit of tens of thousands of static HTML pages that has accumulated over the years. We will describe the technical and business motivations for the project, provide a technical overview of the Drupal migration, and of the the process challenges in dealing with this volume of content. Finally, we will describe the next set of challenges as we work with their Press to clarify their branding goals and redo the visual identity.
For video, see https://www.youtube.com/watch?v=52gAQDXS8Zc&feature=youtu.be
Cloudant Overview Bluemix Meetup from Lisa NeddamRomeo Kienzler
Cloudant is a fully-managed NoSQL distributed data layer service based on a JSON document store that provides high availability, scalability, simplicity and performance. It uses a flexible schema and scales massively while always being available. Cloudant is an operational data store and NoSQL document database with a simple HTTP API that is fully integrated with mobile devices, big data, cloud and delivery. It provides replication, sync, real-time analytics using MapReduce, full-text search and geospatial capabilities.
Things Every Oracle DBA Needs To Know About The Hadoop EcosystemZohar Elkayam
This is a presentation which was presented in multiple forums (in one way or the other). This is a short introduction for Oracle personal (DBAs and DB Developers) for Big Data and the Hadoop Ecosystem.
In the agenda:
• What is the Big Data challenge?
• A Big Data Solution: Apache Hadoop
• HDFS
• MapReduce and YARN
• Hadoop Ecosystem: HBase, Sqoop, Hive, Pig and other tools
• Another Big Data Solution: Apache Spark
• Where does the DBA fits in?
This presentation was presented in DOAG 2016, HROUG 2016, BGOUG 2016, ILOUG Tech Days 2016 and other small private sessions (Israel Technology Police leaders, CIO forum, Amdocs, and others).
The document provides an overview of Couchbase's NoSQL document database capabilities for interactive applications. It discusses Couchbase's leadership in the NoSQL market, common use cases where NoSQL is a good fit like mobile apps and caching, and how Couchbase allows for JSON data everywhere from devices to servers. Relational databases are compared to Couchbase, with Couchbase able to scale out more easily to very large datasets and workloads.
Sql Server Tuning for SharePoint : what every consultant must know (Office 36...serge luca
This document discusses tuning SQL Server for SharePoint. It covers operating system settings like NTFS allocation units and IOPS requirements. SQL Server configuration topics include using a dedicated SQL instance, database recovery models, tempdb settings, and file placement. Database concepts explained include SharePoint database types and SQL Server integration. SQL Server optimization techniques like resource governor and performance counters are also outlined. High availability and disaster recovery options like Always On Availability Groups are then covered.
This document provides an overview and agenda for a presentation on business intelligence and big data technologies. The presentation covers tools such as Excel, PowerPivot, Power View, Reporting Services, PerformancePoint, and HDInsight for working with data from sources like SQL Server, Oracle, DB2, and Hadoop. It discusses self-service BI capabilities and how these tools work with the Microsoft BI stack and platform.
This document provides tips and best practices for configuring ArcGIS Open Data services and sites. Key recommendations include:
- Preparing data by adding attribute aliases and hiding unnecessary fields.
- Configuring services with a max record count under 5,000, enabling WMS/WFS/WCS where applicable, and organizing datasets into multiple services with no more than 20 datasets each.
- Structuring the ArcGIS Online organization with appropriate user roles, staging groups, and registering individual layers to control metadata.
- Customizing the site design through header CSS, placing categories and groups on homepage, and adding contact information.
Maria db 10 and the mariadb foundation(colin)kayokogoto
This document provides an overview of MariaDB 10 and the MariaDB Foundation. It discusses the history and development of MariaDB, including key features added in versions 5.1 through 10.0 such as new storage engines, performance improvements, and features backported from MySQL. It outlines the goals of MariaDB to be compatible with MySQL while adding new features, and describes the community-led development model. The roadmap aims to have MariaDB be a drop-in replacement for MySQL 5.6 by releasing version 10.1.
Slides: NoSQL Data Modeling Using JSON Documents – A Practical ApproachDATAVERSITY
After three decades of relational data modeling, everyone’s pretty comfortable with schemas, tables, and entity-relationships. As more and more Global 2000 companies choose NoSQL databases to power their Digital Economy applications, they need to think about how to best model their data. How do they move from a constrained, table-driven model to an agile, flexible data model based on JSON documents?
This webinar is intended for architects and application developers who want to learn about new JSON document data modeling approaches, techniques, and best practices. This webinar will show you how to get started building a JSON document data model, how to migrate a table-based data model to JSON documents, and how to optimize your design to enable fast query performance.
This webinar will provide practical, experience-based advice and best practices for modeling JSON documents, including:
- When to embed or not embed objects in your JSON document
- Data modeling using a practical data access pattern approach
- Indexing your JSON documents
- Querying your data using N1QL (SQL for JSON)
This document introduces Couchbase, an open-source distributed operational database. It discusses how Couchbase provides scalability and high performance through its architecture which allows independent scaling of data, querying, and indexing workloads. It also highlights Couchbase capabilities like JSON document storage, N1QL querying, asynchronous writes, SDKs, full-text search, and cross data center replication. Examples of Couchbase uses at large companies like eBay are also presented.
The Why, When, and How of NoSQL - A Practical ApproachDATAVERSITY
More and more Fortune 1000 companies like Marriott, Cars.com, Gannett, and PayPal are choosing NoSQL over relational databases like Oracle, SQL Server, and DB2 to power their web, mobile, and IoT applications. Why? Lower costs, higher performance and availability, better agility, and easier scalability. According to The Forrester Wave™: Big Data NoSQL, Q3 2016 report, “NoSQL is no longer an option.” Come see why.
This webinar is intended for developers, architects, and database engineers who are considering NoSQL as an alternative to relational databases. If you’re looking to add NoSQL to your environment, this webinar will show you how to get started and avoid potential pitfalls.
You’ll get practical advice, including:
•Key considerations in moving from relational to NoSQL
•How to identify applications that benefit most from NoSQL
•Data modeling and querying with NoSQL
•Migrating your data to NoSQL
•Best practices for making the switch
This presentation was given by David Maier @magicable @munichnosql may 2014. The code can be found https://github.com/dmaier-couchbase/cbl-android-tasklist
Developing Applications with Go and NoSQLNic Raboy
This document discusses developing applications with Go and NoSQL databases. It covers creating a web application with Go, using Go multiplexers like Gorilla Mux, using the Couchbase NoSQL database including Couchbase Lite, Sync Gateway and Couchbase Server, installing and configuring Couchbase, using the Couchbase Go SDK, querying documents with N1QL, and importing data with Go. It provides the Couchbase developer resources and GitHub code for further reference.
The document provides an overview of Kafka & Couchbase integration patterns. It introduces Couchbase and Kafka, describes how Kafka Connect enables real-time data pipelines between data systems, and how the Couchbase Kafka connector integrates Couchbase with Kafka pipelines. Use cases for the connector include using Couchbase as a data source or sink within Kafka streams. The document concludes with demos of Couchbase as a source and sink using the connector.
Stream your Operational Data with Apache Spark & Kafka into Hadoop using Couc...Data Con LA
Abstract:-
Tracking user events as they happen can challenge anyone providing real time user interaction. It can demand both huge scale and a lot of processing to support dynamic adjustment to targeting products and services. As the operational data store Couchbase data services are capable of processing tens of millions of updates a day. Streaming through systems such as Apache Spark and Kafka into Hadoop, information about these key events can be turned into deeper knowledge. We will review Lambda architectures deployed at sites like PayPal, Live Person and LinkedIn that leverage a Couchbase Data Pipeline.
Bio:-
Justin Michaels. With over 20 years experience in deploying mission critical systems, Justin Michaels industry experience covers capacity planning, architecture and industry vertical experience. Justin brings his passion for architecting, implementing and improving Couchbase to the community as a Solution Architect. His expertise involves both conventional application platforms as well as distributed data management systems. He regularly engages with existing and new Couchbase customers in performance reviews, architecture planning and best practice guidance.
Elasticsearch + Cascading for Scalable Log ProcessingCascading
Supreet Oberoi's presentation on "Large scale log processing with Cascading & Elastic Search". Elasticsearch is becoming a popular platform for log analysis with its ELK stack: Elasticsearch for search, Logstash for centralized logging, and Kibana for visualization. Complemented with Cascading, the application development platform for building Data applications on Apache Hadoop, developers can correlate at scale multiple log and data streams to perform rich and complex log processing before making it available to the ELK stack.
Billions of Messages in Real Time: Why Paypal & LinkedIn Trust an Engagement ...confluent
(Bruno Simic, Solutions Engineer, Couchbase)
Breakout during Confluent’s streaming event in Munich. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
This document discusses semantic annotation using custom vocabularies. It introduces Gabriel Dragomir and provides background on semantic web and linked data. It then describes Apache Stanbol, a framework for semantic annotation of documents. Stanbol allows modular processing of documents using configurable workflows and vocabularies. The document outlines Stanbol's architecture and components. It also discusses integrating Stanbol with Drupal for semantic indexing and annotation of content. A demo is proposed to index Drupal data in Stanbol and annotate entities using DBPedia and a custom semantic web vocabulary.
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
Decoupling Drupal 8.x: Drupal’s Web Services Today and TomorrowAcquia
To much fanfare, Drupal 8 was released in 2015 with web services capabilities off the shelf. But that doesn’t mean our work finished there; the community, thanks to the hard work of the API-first initiative team, has been actively addressing new changes in the surrounding world of web services. The two intervening minor versions of Drupal 8 since 2015 are chock full of improvements.
Even so, the wider web services landscape is rapidly shifting, and new approaches and ideas are quickly gaining momentum in an increasingly diverse landscape. For instance, in the front-end world, particularly in the JavaScript community, emerging specifications such as JSON API and GraphQL are overturning our long-held perceptions about what a web services API is capable of.
Key topics covered in this tech talk include:
How Drupal’s web services have evolved and progressed since the release of Drupal 8
How the wider landscape of web services has shifted around us
How we’re securing Drupal’s place at the vanguard of API-first content management
What’s most relevant to you as a decoupled app developer in Drupal 8.1, 8.2, and 8.3
In Apache Cassandra Lunch #119, Rahul Singh will cover a refresher on GUI desktop/web tools for users that want to get their hands dirty with Cassandra but don't want to deal with CQLSH to do simple queries. Some of the tools are web-based and others are installed on your desktop. Since the beginning days of Cassandra, a lot has changed and there are many options for command-line-haters to use Cassandra.
MongoDB Days UK: Building an Enterprise Data Fabric at Royal Bank of Scotland...MongoDB
Presented by Michael Fulke, Development Team Lead, Royal Bank of Scotland
Experience level: Beginner
When addressing common investment banking use-cases, incumbent application architectures have proven themselves to be complex, difficult to maintain and expensive. Driven by the apparently competing pressures of cost and agility, RBS used MongoDB to build a common enterprise data fabric which is underpinning several core trading platforms. In this session, you will learn how RBS has successfully integrated MongoDB into a wider Java-based architecture, built with a strong open source bias.
Couchbase Server is a NoSQL database that allows developers to build applications with agility and scale them to any size. It provides a flexible JSON schema, fast document storage and retrieval using document IDs, and various data access methods like views, global secondary indexes, and the N1QL query language. Couchbase supports many development frameworks and platforms, and can be deployed in various environments including Docker. It provides features like auto-sharding of data across nodes, replication, and cross data center replication for high availability and disaster recovery.
This document provides an overview of latest developments at H2O.ai, including enhancements to their machine learning platform H2O such as Deep Water for distributed deep learning using GPUs, xgboost integration, stacked ensembles, automatic machine learning, and model interpretation capabilities. It also discusses H2O's community involvement through meetup groups and conferences like PyData.
The initiation of The Hadoop Apache Hive began in 2007 by Facebook due to its data growth.
This ETL system began to fail over few years as more people joined Facebook.
In August 2008, Facebook decided to move to scalable a more scalable open-source Hadoop environment; Hive
Facebook, Netflix and Amazons support the Apache Hive SQL now known as the HiveQL
Cloud Foundry and OpenStack - A Marriage Made in Heaven! (Cloud Foundry Summi...VMware Tanzu
Business Track presented by Animesh Singh, Lead Architect and Strategist at IBM.
Bring the world's best IaaS to the world's best PaaS, In this talk IBM and Rackspace are going to share their experiences of running Cloud Foundry on OpenStack. The talk will focus on how CloudFoundry and OpenStack complement each other, how they technically integrate using Cloud provider interface (CPI), how could we automate OpenStack setup for Cloud Foundry deployments, and what are some of the best practices for configuring a scalable environment.
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