New generations of database technologies are allowing organizations to build applications never before possible, at a speed and scale that were previously unimaginable. MongoDB is the fastest growing database on the planet, and the new 3.2 release will bring the benefits of modern database architectures to an ever broader range of applications and users.
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDBMongoDB
Presented by Achille Brighton, Principal Consulting Engineer, MongoDB
Experience level: Deep dive
MongoDB 3.2 brings major enhancements. New pluggable storage engines optimized for in-memory computing and the most security-sensitive applications. Simplified data governance with document validation, coupled with GUI-based schema discovery and visualization. Improved operational efficiency with enhanced management platforms, continuous uptime across distributed, multi-region deployments, and zero-downtime upgrades. To take advantage of these features, your team needs an upgrade plan. In this session, we’ll walk you through how to build an upgrade plan. We’ll show you how to validate your existing deployment, build a test environment with a representative workload, and detail how to carry out the upgrade. You’ll walk away confident that you're prepared to upgrade.
This presentation contains a preview of MongoDB 3.2 upcoming release where we explore the new storage engines, aggregation framework enhancements and utility features like document validation and partial indexes.
MongoDB San Francisco 2013: Storing eBay's Media Metadata on MongoDB present...MongoDB
This session will be a case study of eBay’s experience running MongoDB for project Zoom, in which eBay stores all media metadata for the site. This includes references to pictures of every item for sale on eBay. This cluster is eBay's first MongoDB installation on the platform and is a mission critical application. Yuri Finkelstein, an Enterprise Architect on the team, will provide a technical overview of the project and its underlying architecture.
How Thermo Fisher is Reducing Data Analysis Times from Days to Minutes with M...MongoDB
Speaker: Joseph Fluckiger, Senior Software Architect, ThermoFisher Scientific
Level: 200 (Intermediate)
Track: Atlas
Mass spectrometry is the gold standard for determining chemical compositions, with spectrometers often measuring the mass of a compound down to a single electron. This level of granularity produces an enormous amount of hierarchical data that doesn't fit well into rows and columns. In this talk, learn how Thermo Fisher is using MongoDB Atlas on AWS to allow their users to get near real-time insights from mass spectrometry experiments – a process that used to take days. We also share how the underlying database service used by Thermo Fisher was built on AWS.
What You Will Learn:
- How we modeled mass spectrometry data to enable us to write and read an enormous about of experimental data efficiently.
- Learn about the best MongoDB tools and patterns for .NET applications.
- Live demo of scaling a MongoDB Atlas cluster with zero down time and visualizing live data from a million dollar Mass Spectrometer stored in MongoDB.
NoSQL datastores fall under the following categories: Key-value stores, document databases, column-family stores and graph databases. The traditional TPC-* tests are not sufficient for these heterogeneous database systems. MongoDB, CouchDB, Cassandra, HBase, Memcaches etc belong to one of 4 families and a common workload can be generated by ycsb to simulate your usecase and benchmark them.
MongoDB Certification Study Group - May 2016Norberto Leite
Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB
MongoDB Introduction talk at Dr Dobbs Conference, MongoDB Evenings at Bangalo...Prasoon Kumar
MongoDB is a leading nosql database. It is horizonatally scalable, document datastore. In this introduction given at Dr Dobbs Conference, Bangalore and Pune in April 2014, I show schema design with an example blog application and Python code snippets. I delivered the same in the maiden MongoDB Evening event at Delhi and Gurgaon in May 2014.
When constructing a data model for your MongoDB collection for CMS, there are various options you can choose from, each of which has its strengths and weaknesses. The three basic patterns are:
1.Store each comment in its own document.
2.Embed all comments in the “parent” document.
3.A hybrid design, stores comments separately from the “parent,” but aggregates comments into a small number of documents, where each contains many comments.
Code sample and wiki documentation is available on https://github.com/prasoonk/mycms_mongodb/wiki.
MongoDB 2.6 is the biggest MongoDB release ever. In this presentation you are going to explore which features, improvements and capabilities were added to the latest version and how you can smoothly upgrade your deployments.
MongoDB Days Silicon Valley: Best Practices for Upgrading to MongoDBMongoDB
Presented by Achille Brighton, Principal Consulting Engineer, MongoDB
Experience level: Deep dive
MongoDB 3.2 brings major enhancements. New pluggable storage engines optimized for in-memory computing and the most security-sensitive applications. Simplified data governance with document validation, coupled with GUI-based schema discovery and visualization. Improved operational efficiency with enhanced management platforms, continuous uptime across distributed, multi-region deployments, and zero-downtime upgrades. To take advantage of these features, your team needs an upgrade plan. In this session, we’ll walk you through how to build an upgrade plan. We’ll show you how to validate your existing deployment, build a test environment with a representative workload, and detail how to carry out the upgrade. You’ll walk away confident that you're prepared to upgrade.
This presentation contains a preview of MongoDB 3.2 upcoming release where we explore the new storage engines, aggregation framework enhancements and utility features like document validation and partial indexes.
MongoDB San Francisco 2013: Storing eBay's Media Metadata on MongoDB present...MongoDB
This session will be a case study of eBay’s experience running MongoDB for project Zoom, in which eBay stores all media metadata for the site. This includes references to pictures of every item for sale on eBay. This cluster is eBay's first MongoDB installation on the platform and is a mission critical application. Yuri Finkelstein, an Enterprise Architect on the team, will provide a technical overview of the project and its underlying architecture.
How Thermo Fisher is Reducing Data Analysis Times from Days to Minutes with M...MongoDB
Speaker: Joseph Fluckiger, Senior Software Architect, ThermoFisher Scientific
Level: 200 (Intermediate)
Track: Atlas
Mass spectrometry is the gold standard for determining chemical compositions, with spectrometers often measuring the mass of a compound down to a single electron. This level of granularity produces an enormous amount of hierarchical data that doesn't fit well into rows and columns. In this talk, learn how Thermo Fisher is using MongoDB Atlas on AWS to allow their users to get near real-time insights from mass spectrometry experiments – a process that used to take days. We also share how the underlying database service used by Thermo Fisher was built on AWS.
What You Will Learn:
- How we modeled mass spectrometry data to enable us to write and read an enormous about of experimental data efficiently.
- Learn about the best MongoDB tools and patterns for .NET applications.
- Live demo of scaling a MongoDB Atlas cluster with zero down time and visualizing live data from a million dollar Mass Spectrometer stored in MongoDB.
NoSQL datastores fall under the following categories: Key-value stores, document databases, column-family stores and graph databases. The traditional TPC-* tests are not sufficient for these heterogeneous database systems. MongoDB, CouchDB, Cassandra, HBase, Memcaches etc belong to one of 4 families and a common workload can be generated by ycsb to simulate your usecase and benchmark them.
MongoDB Certification Study Group - May 2016Norberto Leite
Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB
MongoDB Introduction talk at Dr Dobbs Conference, MongoDB Evenings at Bangalo...Prasoon Kumar
MongoDB is a leading nosql database. It is horizonatally scalable, document datastore. In this introduction given at Dr Dobbs Conference, Bangalore and Pune in April 2014, I show schema design with an example blog application and Python code snippets. I delivered the same in the maiden MongoDB Evening event at Delhi and Gurgaon in May 2014.
When constructing a data model for your MongoDB collection for CMS, there are various options you can choose from, each of which has its strengths and weaknesses. The three basic patterns are:
1.Store each comment in its own document.
2.Embed all comments in the “parent” document.
3.A hybrid design, stores comments separately from the “parent,” but aggregates comments into a small number of documents, where each contains many comments.
Code sample and wiki documentation is available on https://github.com/prasoonk/mycms_mongodb/wiki.
MongoDB 2.6 is the biggest MongoDB release ever. In this presentation you are going to explore which features, improvements and capabilities were added to the latest version and how you can smoothly upgrade your deployments.
Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.
eHarmony - Messaging Platform with MongoDB Atlas MongoDB
Speaker: Elankumaran Srinivasan, Senior Software Engineer, eHarmony
Speaker: Vijay Vangapandu, Senior Principal Software Engineer, eharmony
Communication is an integral part of the dating process. The more users communicate on our platform, the higher the chances they will find someone they like.
By early August 2016 reports indicated a steep decline in communication rates. The multi-step, turn by turn communication process was no longer enticing to the users in the current world where real time messaging is a norm. The existing store and design was not conducive to moving in this direction given its rigid nature and slow response times. Change was imminent.
User communication being a high traffic feature, the store was the crux. The data store had to be robust, scalable and flexible enough to support current and future needs. Store performance could not be a bottleneck and its failure was not an option. Our team was lean and had no experience with MongoDB, let alone setting up a cluster and managing one. Also, given this was a new system, traffic patterns and capacity could not be predicted.
In this presentation, we will cover how eHarmony was able to leverage MongoDB Atlas to overcome the above challenges to build a highly successful real time communication system for its users.
Big Data Day LA 2016/ NoSQL track - MongoDB 3.2 Goodness!!!, Mark Helmstetter...Data Con LA
This talk explores the new features of MongoDB 3.2 such as $lookup, document validation rules, encryption-at-rest and tools like the BI Connector, OpsManager 2.0 and Compass.
Webinar: “ditch Oracle NOW”: Best Practices for Migrating to MongoDBMongoDB
This webinar will guide you through the best practices for migrating off of a relational database. Whether you are migrating an existing application, or considering using MongoDB in place of your traditional relational database for a new project, this webinar will get you to production faster, with less effort, cost and risk.
One of MongoDB’s primary attractions for developers is that it gives them the ability to start application development without needing to define a formal, up-front schema. Operations teams appreciate the fact that they don't need to perform a time-consuming schema upgrade operation every time the developers need to store a different attribute.
Some projects reach a point where it's necessary to define rules on what's being stored in the database. This webinar explains how MongoDB 3.2 allows that document validation work to be performed by the database rather than in the application code.
This webinar focuses on the benefits of using document validation: how to set up the rules using the familiar MongoDB Query Language and how to safely roll it out into an existing, mature production environment.
MMS - Monitoring, backup and management at a single clickMatias Cascallares
MongoDB Management Service (MMS) makes operations effortless, reducing complicated tasks in big deployments to a couple of clicks. You can monitor, backup and manage your replica sets and sharded clusters through the MMS interface. In this presentation we are going to explore how to setup, use and get the best of MMS.
Webinar: Choosing the Right Shard Key for High Performance and ScaleMongoDB
Read these webinar slides to learn how selecting the right shard key can future proof your application.
The shard key that you select can impact the performance, capability, and functionality of your database.
MongoDB is a leading database technology that combines the foundations of RDBMS with the innovations of NoSQL, allowing organizations to simultaneously boost productivity and lower TCO.
MongoDB Enterprise Advanced is a finely-tuned package of advanced software, enterprise-grade support, and other services designed to accelerate your success with MongoDB in every stage of your app lifecycle, from early development to the scale-out of mission-critical production environments.
With the release of 3.2, MongoDB Enterprise Advanced now includes:
MongoDB Ops Manager 2.0
MongoDB Compass, the MongoDB GUI
MongoDB Connector for Business Intelligence
Encrypted Storage Engine
In-Memory Storage Engine (beta)
Attend this webinar to learn how MongoDB Enterprise Advanced can help you get to market faster and de-risk your mission critical deployments.
Building a Scalable and Modern Infrastructure at CARFAXMongoDB
The CARFAX vehicle history database contains over twelve billion documents in a twelve shard cluster that replicates to multiple data centers. This will be a step by step walk through of how we deploy our servers, manage high volume reads and writes, and our configuration for high availability. By automating everything from the operating system install up we are able deploy complete replica clusters quickly and efficiently. Using distributed processing and message queuing we load millions of new documents each day with a projected growth over a billion records per year. Through the use of tagging, server configuration, and read settings we deliver content with high consistency and availability.
The MongoDB Spark Connector integrates MongoDB and Apache Spark, providing users with the ability to process data in MongoDB with the massive parallelism of Spark. The connector gives users access to Spark's streaming capabilities, machine learning libraries, and interactive processing through the Spark shell, Dataframes and Datasets. We'll take a tour of the connector with a focus on practical use of the connector, and run a demo using both Spark and MongoDB for data processing.
Presented by Claudius Li, Solutions Architect at MongoDB, at MongoDB Evenings New England 2017.
MongoDB Atlas is the premier database as a service offering. Find out how MongoDB Atlas can help your team to deploy more easily, develop faster and easily manage deployment, maintenance, upgrades and expansions. We will also demonstrate some of the key features and tools that come with MongoDB Atlas.
Are you in the process of evaluating or migrating to MongoDB? We will cover key aspects of migrating to MongoDB from a RDBMS, including Schema design, Indexing strategies, Data migration approaches as your implementation reaches various SDLC stages, Achieving operational agility through MongoDB Management Services (MMS).
Joins and Other Aggregation Enhancements Coming in MongoDB 3.2MongoDB
Applications get great efficiency from MongoDB by combining data that is accessed together into a single document. There are however situations where it is more efficient to have references between documents rather than embedding everything into a single document. This led to joins being our most requested feature. MongoDB 3.2 addresses this through the introduction of the $lookup stage in the aggregation pipeline to implement left-outer joins.
This webinar looks at $lookup as well as the other significant aggregation enhancements coming with MongoDB 3.2—why they're needed, what they deliver, and how to use them.
Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.
eHarmony - Messaging Platform with MongoDB Atlas MongoDB
Speaker: Elankumaran Srinivasan, Senior Software Engineer, eHarmony
Speaker: Vijay Vangapandu, Senior Principal Software Engineer, eharmony
Communication is an integral part of the dating process. The more users communicate on our platform, the higher the chances they will find someone they like.
By early August 2016 reports indicated a steep decline in communication rates. The multi-step, turn by turn communication process was no longer enticing to the users in the current world where real time messaging is a norm. The existing store and design was not conducive to moving in this direction given its rigid nature and slow response times. Change was imminent.
User communication being a high traffic feature, the store was the crux. The data store had to be robust, scalable and flexible enough to support current and future needs. Store performance could not be a bottleneck and its failure was not an option. Our team was lean and had no experience with MongoDB, let alone setting up a cluster and managing one. Also, given this was a new system, traffic patterns and capacity could not be predicted.
In this presentation, we will cover how eHarmony was able to leverage MongoDB Atlas to overcome the above challenges to build a highly successful real time communication system for its users.
Big Data Day LA 2016/ NoSQL track - MongoDB 3.2 Goodness!!!, Mark Helmstetter...Data Con LA
This talk explores the new features of MongoDB 3.2 such as $lookup, document validation rules, encryption-at-rest and tools like the BI Connector, OpsManager 2.0 and Compass.
Webinar: “ditch Oracle NOW”: Best Practices for Migrating to MongoDBMongoDB
This webinar will guide you through the best practices for migrating off of a relational database. Whether you are migrating an existing application, or considering using MongoDB in place of your traditional relational database for a new project, this webinar will get you to production faster, with less effort, cost and risk.
One of MongoDB’s primary attractions for developers is that it gives them the ability to start application development without needing to define a formal, up-front schema. Operations teams appreciate the fact that they don't need to perform a time-consuming schema upgrade operation every time the developers need to store a different attribute.
Some projects reach a point where it's necessary to define rules on what's being stored in the database. This webinar explains how MongoDB 3.2 allows that document validation work to be performed by the database rather than in the application code.
This webinar focuses on the benefits of using document validation: how to set up the rules using the familiar MongoDB Query Language and how to safely roll it out into an existing, mature production environment.
MMS - Monitoring, backup and management at a single clickMatias Cascallares
MongoDB Management Service (MMS) makes operations effortless, reducing complicated tasks in big deployments to a couple of clicks. You can monitor, backup and manage your replica sets and sharded clusters through the MMS interface. In this presentation we are going to explore how to setup, use and get the best of MMS.
Webinar: Choosing the Right Shard Key for High Performance and ScaleMongoDB
Read these webinar slides to learn how selecting the right shard key can future proof your application.
The shard key that you select can impact the performance, capability, and functionality of your database.
MongoDB is a leading database technology that combines the foundations of RDBMS with the innovations of NoSQL, allowing organizations to simultaneously boost productivity and lower TCO.
MongoDB Enterprise Advanced is a finely-tuned package of advanced software, enterprise-grade support, and other services designed to accelerate your success with MongoDB in every stage of your app lifecycle, from early development to the scale-out of mission-critical production environments.
With the release of 3.2, MongoDB Enterprise Advanced now includes:
MongoDB Ops Manager 2.0
MongoDB Compass, the MongoDB GUI
MongoDB Connector for Business Intelligence
Encrypted Storage Engine
In-Memory Storage Engine (beta)
Attend this webinar to learn how MongoDB Enterprise Advanced can help you get to market faster and de-risk your mission critical deployments.
Building a Scalable and Modern Infrastructure at CARFAXMongoDB
The CARFAX vehicle history database contains over twelve billion documents in a twelve shard cluster that replicates to multiple data centers. This will be a step by step walk through of how we deploy our servers, manage high volume reads and writes, and our configuration for high availability. By automating everything from the operating system install up we are able deploy complete replica clusters quickly and efficiently. Using distributed processing and message queuing we load millions of new documents each day with a projected growth over a billion records per year. Through the use of tagging, server configuration, and read settings we deliver content with high consistency and availability.
The MongoDB Spark Connector integrates MongoDB and Apache Spark, providing users with the ability to process data in MongoDB with the massive parallelism of Spark. The connector gives users access to Spark's streaming capabilities, machine learning libraries, and interactive processing through the Spark shell, Dataframes and Datasets. We'll take a tour of the connector with a focus on practical use of the connector, and run a demo using both Spark and MongoDB for data processing.
Presented by Claudius Li, Solutions Architect at MongoDB, at MongoDB Evenings New England 2017.
MongoDB Atlas is the premier database as a service offering. Find out how MongoDB Atlas can help your team to deploy more easily, develop faster and easily manage deployment, maintenance, upgrades and expansions. We will also demonstrate some of the key features and tools that come with MongoDB Atlas.
Are you in the process of evaluating or migrating to MongoDB? We will cover key aspects of migrating to MongoDB from a RDBMS, including Schema design, Indexing strategies, Data migration approaches as your implementation reaches various SDLC stages, Achieving operational agility through MongoDB Management Services (MMS).
Joins and Other Aggregation Enhancements Coming in MongoDB 3.2MongoDB
Applications get great efficiency from MongoDB by combining data that is accessed together into a single document. There are however situations where it is more efficient to have references between documents rather than embedding everything into a single document. This led to joins being our most requested feature. MongoDB 3.2 addresses this through the introduction of the $lookup stage in the aggregation pipeline to implement left-outer joins.
This webinar looks at $lookup as well as the other significant aggregation enhancements coming with MongoDB 3.2—why they're needed, what they deliver, and how to use them.
Content Management with MongoDB by Mark HelmstetterMongoDB
MongoDB is great for content management and delivery across a multitude of apps such as e-commerce websites, online publications, web content management systems (CMS), document management, archives and others. MongoDB's flexible schema and data model make it easy to catalog multiple content types with diverse meta data.
-Schema design for content management
-Using GridFS for storing binary files
-How you can leverage MongoDB's auto-sharding to partition your content across multiple servers
Mongo db - How we use Go and MongoDB by Sam HelmanHakka Labs
In this talk, we'll hear from Sam Helman, Software Engineer at 10gen, on how 10gen is integrating Go into our new and existing cloud tools. Some of the tools leveraging Go include the backup capabilities in MongoDB Management Service and a continuos integration tool. This was an opportunity to experiment with new technologies and create a better product for end users.
Programming the in Go and the mgo driver has been extremely satisfying. Between the lightweight syntax, the first-class concurrency and the well documented, idiomatic libraries such as mgo, Go is a great choice for writing anything from small scripts to large distributed applications. In this talk, Sam will go through how the team has integrated Go and why Go and MongoDB are a great match for cloud services.
One of MongoDB’s primary appeals to developers is that it gives them the ability to start application development without needing to define a formal, up-front schema. Operations teams appreciate the fact that they don't need to perform a time-consuming schema upgrade operation every time the developers need to store a different attribute (as an example, The Weather Channel is now able to launch new features in hours whereas it used to take weeks). For business leaders, the application gets launched much faster, and new features can be rolled out more frequently. MongoDB powers agility.
Some projects reach a point where it's necessary to define rules on what's being stored in the database – for example, that for any document in a particular collection, you can be assured that certain attributes are present.
To address the challenges discussed above, while at the same time maintaining the benefits of a dynamic schema, MongoDB 3.2 introduces document validation.
There is significant flexibility to customize which parts of the documents are **and are not** validated for any collection.
Data Streaming with Apache Kafka & MongoDB - EMEAAndrew Morgan
A new generation of technologies is needed to consume and exploit today's real time, fast moving data sources. Apache Kafka, originally developed at LinkedIn, has emerged as one of these key new technologies.
This webinar explores the use-cases and architecture for Kafka, and how it integrates with MongoDB to build sophisticated data-driven applications that exploit new sources of data.
In the age of digital transformation and disruption, your ability to thrive depends on how you adapt to the constantly changing environment. MongoDB 3.4 is the latest release of the leading database for modern applications, a culmination of native database features and enhancements that will allow you to easily evolve your solutions to address emerging challenges and use cases.
In this webinar, we introduce you to what’s new, including:
- Multimodel Done Right. Native graph computation, faceted navigation, rich real-time analytics, and powerful connectors for BI and Apache Spark bring additional multimodel database support right into MongoDB.
- Mission-Critical Applications. Geo-distributed MongoDB zones, elastic clustering, tunable consistency, and enhanced security controls bring state-of-the-art database technology to your most mission-critical applications.
- Modernized Tooling. Enhanced DBA and DevOps tooling for schema management, fine-grained monitoring, and cloud-native integration allow engineering teams to ship applications faster, with less overhead and higher quality.
Der Talk wurde am 25.09.2013 auf der Java User Group Frankfurt gehalten und gibt einen Überblick und Einstieg in MongoDB aus der Sicht eines Java-Programmierers.
Dabei werden folgende Themen behandelt:
- Buzzword Bingo: NoSQL, Big Data, Horizontale Skalierung, CAP-Theorem, Eventual Consistency
- Übersicht über MongoDB
- Datenmanipulation: CRUD, Aggregation Framework, Map/Reduce
- Indexing
- Konsistenz beim Schreiben und Lesen von Daten
- Java API & Frameworks
In-Memory Storage Engine (beta)
WiredTiger as the default storage engine
Advanced security (encryption at rest)
Document Validation
Advanced full text
Dynamic Lookups
BI Connector (Tableau, Qlikview, Cognos, BusinessObjects, etc...)
Database GUI with MongoDB Compass
And more...
De nouvelles générations de technologies de bases de données permettent aux organisations de créer des applications jusque-là inédites, à une vitesse et une échelle inimaginables auparavant. MongoDB est la base de données qui connaît la croissance la plus rapide au monde. La nouvelle version 3.2 offre les avantages des architectures de bases de données modernes à une gamme toujours plus large d'applications et d'utilisateurs.
MongoDB es la base de datos con más rápido crecimiento del mundo La nueva versión 3.2 extiende los beneficios de las modernas arquitecturas de bases de datos a una gama aun más amplia de aplicaciones y usuarios.
En esta grabación del seminario web presentamos todas las novedades, que incluyen:
● Nuevos motores de almacenamiento conectables.
● Una visión empresarial más rápida con búsquedas y análisis mejorados en tiempo real, combinada con una conectividad fluida a herramientas de BI estándar.
● Gestión de datos simplificado con validación de documentos, junto a una detección y visualización de esquema basadas en una interfaz gráfica.
Mayor eficacia operativa con plataformas de gestión mejoradas, disponibilidad continua en implementaciones multirregionales y distribuidas, y actualizaciones con inactividad cero.
Presented by Rob Walters, Solutions Architect, MongoDB, at MongoDB Evenings New England 2017.
MongoDB 3.6 is the latest version of the world's most popular document database. In this session we will cover the key themes of the release including speed to develop, speed to production and speed to insight. Learn about the key features that support these themes and how you can start leveraging them today!
As an official MongoDB-as-a-Service offering from MongoDB Inc., the maker for MongoDB, Atlas is becoming a very popular service offering for those who wish to build their applications in the cloud, regardless on AWS, Azure or GCP. One less known cloud product offered on the Atlas platform is Stitch, A group of services designed to interact with Atlas in every conceivable way, including creating endpoints, triggers, user authentication flows, serverless functions, and a UI to handle all of this. Adding these together, you have a server-less solution running on top of MongoDB cloud.
This was presented by the MongoDB team at the Singapore VIP event on 24th Jan 2019.
The presentation covers-
What is MongoDB
Why MongoDB
MongoDB As a Service, Serverless Platform and Mobile
MongoDB Atlas: Database as a Service (Available on AWS, Azure and Google Cloud)
Usecases
Webinar: Faster Big Data Analytics with MongoDBMongoDB
Learn how to leverage MongoDB and Big Data technologies to derive rich business insight and build high performance business intelligence platforms. This presentation includes:
- Uncovering Opportunities with Big Data analytics
- Challenges of real-time data processing
- Best practices for performance optimization
- Real world case study
This presentation was given in partnership with CIGNEX Datamatics.
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
During this talk we'll navigate through a customer's journey as they migrate an existing MongoDB deployment to MongoDB Atlas. While the migration itself can be as simple as a few clicks, the prep/post effort requires due diligence to ensure a smooth transfer. We'll cover these steps in detail and provide best practices. In addition, we’ll provide an overview of what to consider when migrating other cloud data stores, traditional databases and MongoDB imitations to MongoDB Atlas.
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB
MongoDB Kubernetes operator and MongoDB Open Service Broker are ready for production operations. Learn about how MongoDB can be used with the most popular container orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications. A demo will show you how easy it is to enable MongoDB clusters as an External Service using the Open Service Broker API for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB
Are you new to schema design for MongoDB, or are you looking for a more complete or agile process than what you are following currently? In this talk, we will guide you through the phases of a flexible methodology that you can apply to projects ranging from small to large with very demanding requirements.
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB
Humana, like many companies, is tackling the challenge of creating real-time insights from data that is diverse and rapidly changing. This is our journey of how we used MongoDB to combined traditional batch approaches with streaming technologies to provide continues alerting capabilities from real-time data streams.
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
Common components of an IoT solution
The challenges involved with managing time-series data in IoT applications
Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB
Our clients have unique use cases and data patterns that mandate the choice of a particular strategy. To implement these strategies, it is mandatory that we unlearn a lot of relational concepts while designing and rapidly developing efficient applications on NoSQL. In this session, we will talk about some of our client use cases, the strategies we have adopted, and the features of MongoDB that assisted in implementing these strategies.
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
Encryption is not a new concept to MongoDB. Encryption may occur in-transit (with TLS) and at-rest (with the encrypted storage engine). But MongoDB 4.2 introduces support for Client Side Encryption, ensuring the most sensitive data is encrypted before ever leaving the client application. Even full access to your MongoDB servers is not enough to decrypt this data. And better yet, Client Side Encryption can be enabled at the "flick of a switch".
This session covers using Client Side Encryption in your applications. This includes the necessary setup, how to encrypt data without sacrificing queryability, and what trade-offs to expect.
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB
MongoDB Kubernetes operator is ready for prime-time. Learn about how MongoDB can be used with most popular orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications.
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB
When you need to model data, is your first instinct to start breaking it down into rows and columns? Mine used to be too. When you want to develop apps in a modern, agile way, NoSQL databases can be the best option. Come to this talk to learn how to take advantage of all that NoSQL databases have to offer and discover the benefits of changing your mindset from the legacy, tabular way of modeling data. We’ll compare and contrast the terms and concepts in SQL databases and MongoDB, explain the benefits of using MongoDB compared to SQL databases, and walk through data modeling basics so you feel confident as you begin using MongoDB.
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB
Query performance should be the unsung hero of an application, but without proper configuration, can become a constant headache. When used properly, MongoDB provides extremely powerful querying capabilities. In this session, we'll discuss concepts like equality, sort, range, managing query predicates versus sequential predicates, and best practices to building multikey indexes.
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB
Aggregation pipeline has been able to power your analysis of data since version 2.2. In 4.2 we added more power and now you can use it for more powerful queries, updates, and outputting your data to existing collections. Come hear how you can do everything with the pipeline, including single-view, ETL, data roll-ups and materialized views.
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB
Are you new to schema design for MongoDB, or are you looking for a more complete or agile process than what you are following currently? In this talk, we will guide you through the phases of a flexible methodology that you can apply to projects ranging from small to large with very demanding requirements.
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB
MongoDB Atlas Data Lake is a new service offered by MongoDB Atlas. Many organizations store long term, archival data in cost-effective storage like S3, GCP, and Azure Blobs. However, many of them do not have robust systems or tools to effectively utilize large amounts of data to inform decision making. MongoDB Atlas Data Lake is a service allowing organizations to analyze their long-term data to discover a wealth of information about their business.
This session will take a deep dive into the features that are currently available in MongoDB Atlas Data Lake and how they are implemented. In addition, we'll discuss future plans and opportunities and offer ample Q&A time with the engineers on the project.
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB
Virtual assistants are becoming the new norm when it comes to daily life, with Amazon’s Alexa being the leader in the space. As a developer, not only do you need to make web and mobile compliant applications, but you need to be able to support virtual assistants like Alexa. However, the process isn’t quite the same between the platforms.
How do you handle requests? Where do you store your data and work with it to create meaningful responses with little delay? How much of your code needs to change between platforms?
In this session we’ll see how to design and develop applications known as Skills for Amazon Alexa powered devices using the Go programming language and MongoDB.
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB
aux Core Data, appréciée par des centaines de milliers de développeurs. Apprenez ce qui rend Realm spécial et comment il peut être utilisé pour créer de meilleures applications plus rapidement.
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB
Il n’a jamais été aussi facile de commander en ligne et de se faire livrer en moins de 48h très souvent gratuitement. Cette simplicité d’usage cache un marché complexe de plus de 8000 milliards de $.
La data est bien connu du monde de la Supply Chain (itinéraires, informations sur les marchandises, douanes,…), mais la valeur de ces données opérationnelles reste peu exploitée. En alliant expertise métier et Data Science, Upply redéfinit les fondamentaux de la Supply Chain en proposant à chacun des acteurs de surmonter la volatilité et l’inefficacité du marché.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Webinar: What's New in MongoDB 3.2
1. What’s New in MongoDB 3.2
Mat Keep
Director, Product Marketing, MongoDB
Andrew Morgan
Principal Product Marketing Manager, MongoDB
2. MongoDB 3.2 – a BIG Release
Hash-Based Sharding
Roles
Kerberos
On-Prem Monitoring
2.2 2.4 2.6 3.0 3.2
Agg. Framework
Location-Aware Sharding
$out
Index Intersection
Text Search
Field-Level Redaction
LDAP & x509
Auditing
Document Validation
Fast Failover
Simpler Scalability
Aggregation ++
Encryption At Rest
In-Memory Storage
Engine
BI Connector
$lookup
MongoDB Compass
APM Integration
Profiler Visualization
Auto Index Builds
Backups to File System
Doc-Level Concurrency
Compression
Storage Engine API
≤50 replicas
Auditing ++
Ops Manager
3. Themes
Broader use case portfolio. Pluggable storage engine strategy enables us to
rapidly cover more use cases with a single database.
Mission-critical apps. MongoDB delivers major advances in the critical areas
of governance, high availability, and disaster recovery.
New tools for new users. Now MongoDB is an integral part of the tooling and
workflows of Data Analysts, DBAs, and Operations teams.
7. WiredTiger is the New Default
WiredTiger – widely deployed with 3.0 – is
now the default storage engine for
MongoDB.
• Best general purpose storage engine
• 7-10x better write throughput
• Up to 80% compression
9. Encrypted Storage Engine
Encrypted storage engine for end-to-end
encryption of sensitive data in regulated
industries
• Reduces the management and performance
overhead of external encryption mechanisms
• AES-256 Encryption, FIPS 140-2 option available
• Key management: Local key management via
keyfile or integration with 3rd party key
management appliance via KMIP
• Based on WiredTiger storage engine
• Requires MongoDB Enterprise Advanced
10. “Protecting sensitive data assets is one of most important things
we do. The new Database Encryption feature in MongoDB 3.2 is a
significant step forward in allowing us to more simply add
encryption at-rest to our list of security controls.
In our tests, we found the new database encryption feature easy
to enable, stable and consistent with our performance
expectations.”
Shawn Drew
Data Integration Solutions Architect
University of Washington
12. In-Memory Storage Engine (Beta)
Handle ultra-high throughput with low
latency and high availability
• Delivers the extreme throughput and predictable
latency required by the most demanding apps in
Adtech, finance, and more.
• Achieve data durability with replica set members
running disk-backed storage engine
• Available for beta testing and is expected for GA in
early 2016
15. A 10% improvement in data usability
at a Fortune 1000 company could
increase revenues by $2 BN per year
Source: University of Texas, Austin
16. Data Governance with Document Validation
Implement data governance without
sacrificing agility that comes from dynamic
schema
• Enforce data quality across multiple teams and
applications
• Use familiar MongoDB expressions to control
document structure
• Validation is optional and can be as simple as a
single field, all the way to every field, including
existence, data types, and regular expressions
17. Document Validation Example
The example on the left adds a rule to the
contacts collection that validates:
• The year of birth is no later than 1994
• The document contains a phone number and / or
an email address
• When present, the phone number and email
addresses are strings
18. “Rocket.Chat and our other applications need to be able to quickly
access various types of data to provide a seamless solution for our
users.
With MongoDB 3.2, we will now be able to implement the data
governance we’re seeking, without sacrificing agility that comes from
dynamic schema. The newfound ability to use familiar MongoDB
expression syntax to control document structure, rather than learning a
whole new language or process, is key for us.”
Gabriel Engel
Founder and CEO
Rocket.Chat
19. Enhancements for your mission-critical apps
More improvements in 3.2 that optimize the
database for your mission-critical
applications
• Meet stringent SLAs with Raft-base fast-failover
algorithm
– Under 2 seconds to detect and recover from
replica set primary failure
– Enhanced durability through write conerns
• Simplified management of sharded clusters
allow you to easily scale to many data centers
– Config servers are now deployed as replica
sets; up to 50 members/locations
21. For Business Analysts & Data Scientists
MongoDB 3.2 allows business analysts and
data scientists to support the business with
new insights from untapped data sources
• MongoDB Connector for BI
• Dynamic Lookup
• New Aggregation Operators & Improved Text
Search
23. MongoDB Connector for BI
Visualize and explore multi-dimensional
documents using SQL-based BI tools. The
connector does the following:
• Provides the BI tool with the schema of the
MongoDB collection to be visualized
• Translates SQL statements issued by the BI tool
into equivalent MongoDB queries that are sent to
MongoDB for processing
• Converts the results into the tabular format
expected by the BI tool, which can then visualize
the data based on user requirements
24. “We are thrilled to enable Tableau users, who traditionally work with their
relational data, to fully integrate the multi-structured data stored in the
database powering modern applications via the new MongoDB BI Connector”
Jeffrey Feng
Product Manager
Tableau Software
25. Dynamic Lookup
Combine data from multiple collections with
left outer joins for richer analytics & more
flexibility in data modeling
• Blend data from multiple collections for analysis
• Higher performance analytics with less application-
side code and less effort from your developers
• Executed via the new $lookup operator, a stage in
the MongoDB Aggregation Framework pipeline
26. “I am most excited by the dynamic lookups coming in MongoDB 3.2. The ability
to more easily join customer data with 3rd-party data feeds gives us more
flexibility in data modeling, and simplifies the real-time analytics we rely on to
constantly improve our value to our customers.”
David Strickland
CTO
MyDealerLot
35. Improved In-Database Analytics & Search
New Aggregation operators extend options for
performing analytics and ensure that answers
are delivered quickly and simply with lower
developer complexity
• Array operators: $slice, $arrayElemAt, $concatArrays,
$filter, $min, $max, $avg, $sum, and more
• New mathematical operators: $stdDevSamp,
$stdDevPop, $sqrt, $abs, $trunc, $ceil, $floor, $log,
$pow, $exp, and more
• Random sample of documents: $sample
• Case sensitive text search and support for additional
languages such as Arabic, Farsi, Chinese, and more
36. For Database Administrators
MongoDB 3.2 helps users in your
organization understand the data in your
database
• MongoDB Compass
– For DBAs responsible for maintaining the
database in production
– No knowledge of the MongoDB query
language required
37. MongoDB Compass
For fast schema discovery and visual
construction of ad-hoc queries
• Visualize schema
– Frequency of fields
– Frequency of types
– Determine validator rules
• View Documents
• Graphically build queries
• Authenticated access
39. Up to 80% of TCO is driven by
on-going operations and
maintenance costs
Source: Gartner
40. For Operations Teams
MongoDB 3.2 simplifies and enhances
MongoDB’s management platforms. Ops
teams can be 10-20x more productive using
Ops and Cloud Manager to run MongoDB.
• Start from a global view of infrastructure:
Integrations with Application Performance
Monitoring platforms
• Drill down: Visual query performance diagnostics,
index recommendations
• Then, deploy: Automated index builds
• Refine: Partial indexes improve resource
utilization
41. Integrations with APM Platforms
Easily incorporate MongoDB performance
metrics into your existing APM dashboards
for global oversight of your entire IT stack
• MongoDB drivers enhanced with new API that
exposes query performance metrics to APM tools
• Packaged integration with Cloud Manager to
visualize server metrics
• Deep dive with Ops and Cloud Manager offering
rich database monitoring & tools for common
operations tasks
42. “We've been really excited to work with MongoDB on enhancing their APM
integration with the New Relic platform. MongoDB has become an integral
part of the tooling and workflows of DBAs and Operations teams and we
expect the trend to increase.
To support MongoDB 3.2, we jointly-developed an integration between
MongoDB Ops Manager and New Relic APM, Insights, and Plugins. These
integrations mean MongoDB health can now be monitored alongside the rest
of the application estate.".”
Cooper Marcus
Senior Product Manager
New Relic.
43. Query Perf. Visualizations & Optimization
Fast and simple query optimization with the
new Visual Query Profiler
• Query and write latency are consolidated and
displayed visually; your ops teams can easily
identify slower queries and latency spikes
• Visual query profiler analyzes the data it displays
and provides recommendations for new indexes
that can be created to improve query performance
• Ops Manager and Cloud Manager can automate
the rollout of new indexes, reducing risk and your
team’s operational overhead
44. “I’m excited by the availability of Visual Query Profiler in Ops Manager &
Cloud Manager. It helps us tremendously improve the performance of our
database by identifying queries that are slowing us down and provides
recommendations for new indexes -- which it can then build through a rolling
index build.”
Daniel Rubio
Director
Mondo Sports Ltd
45. Refine with Partial Indexes
Balance delivering good query performance
while consuming fewer system resources
• Specify a filtering expression during index creation
to instruct MongoDB to only include documents
that meet your desired conditions
• The example to the left creates a compound index
that only indexes the documents with the rating
field greater than 5
46. Ops Manager Enhancements
3.2 includes Ops Manager enhancements to
improve the productivity of your ops teams and
further simplify installation and management
• MongoDB backup on standard network-mountable filesystems;
integrates with your existing storage infrastructure
• Automated database restores; Build clusters from backup in a
few clicks
• Faster time to first database snapshot
• Support for maintenance windows
• Centralized UI for installation and config of all application and
backup components
47. Next Steps
• Download the Whitepaper
– https://www.mongodb.com/collateral/mongodb-3-2-whats-new
• Read the Release Notes
– https://docs.mongodb.org/manual/release-notes/3.2/
• Not yet ready for production but download and try!
– https://www.mongodb.org/downloads#development
• Detailed blogs
– https://www.mongodb.com/blog/
• Feedback
– MongoDB 3.2 Bug Hunt
• https://www.mongodb.com/blog/post/announcing-the-mongodb-3-2-bug-hunt
– https://jira.mongodb.org/
DISCLAIMER: MongoDB's product plans are for informational purposes only. MongoDB's plans may
change and you should not rely on them for delivery of a specific feature at a specific time.
49. Conceptual Model ofAggregation Framework
Start with the original collection; each record
(document) contains a number of shapes (keys),
each with a particular color (value)
• $match filters out documents that don’t contain a
red diamond
• $project adds a new “square” attribute with a value
computed from the value (color) of the snowflake
and triangle attributes
50. Conceptual Model ofAggregation Framework
• $lookup performs a left outer join with another
collection, with the star being the comparison key
• Finally, the $group stage groups the data by the
color of the square and produces statistics for
each group
Editor's Notes
And its getting worse!
Research from PWC – 66% CAGR since 2009
48% increase in 2014 over 2013
It’s also worth noting that the number of respondents reporting losses of $20 million or more almost doubled over 2013.
Other research, 96% came from theft of database records
As illustrated by the ecommerce example above, user data is managed by the In-Memory engine to provide the throughput and bounded latency essential for great customer experience. However, the product catalog’s data storage requirements exceed server memory capacity, so is provisioned to another MongoDB replica set configured with the disk-based WiredTiger storage engine.
In this example, MongoDB’s flexible storage architecture means developers are freed from the complexity of having to use different in-memory and disk-based databases to support the e-commerce application. Administrators are freed from the complexity of having to configure and manage separate data layers. Instead, the application uses the same MongoDB database with each service powered by the storage engine best optimized for the use case.
Projection should create a new key rather than removing some
Projection should create a new key rather than removing some
Projection should create a new key rather than removing some
Projection should create a new key rather than removing some
Projection should create a new key rather than removing some
Projection should create a new key rather than removing some
Projection should create a new key rather than removing some
Projection should create a new key rather than removing some
Determine validator rules: You can use the tool to figure out what you want to set as validation rules
Determine validator rules: You can use the tool to figure out what you want to set as validation rules
$lookup – this creates new documents which contain everything from the previous stage but augmented with data from any document from the second collection containing a matching colored star (i.e., the blue and yellow stars had matching lookup values, whereas the red star had none)