The document describes a conference on accelerating a path to digital transformation with a cloud data strategy. It provides an agenda for the conference including speakers on executing a cloud data strategy, customer stories from De Persgroep and Toyota Motor Europe, and a session on landing in the cloud with MongoDB Atlas. The document also provides background on the speakers and their companies.
[MongoDB.local Bengaluru 2018] Jumpstart: Introduction to Schema DesignMongoDB
Presented by: Saurabh Kashikar
Abstract: MongoDB’s basic unit of storage is a document. Documents can represent rich, schema-free data structures, meaning that we have several viable alternatives to the normalized, relational model. If you are new to MongoDB, learn the schema design basics in this introductory session. This session will help you model basic relationships in MongoDB.
What You Will Learn:
- The fundamentals of the MongoDB document model.
- How to model 1-1 and one-to-many (1-N) relationships in MongoDB.
- How to model many-to-many (N-N) relationships in MongoDB.
[MongoDB.local Bengaluru 2018] The Path to Truly Understanding Your MongoDB DataMongoDB
Presented by: Vivek Singh
Abstract: Do you want to run analytics on your MongoDB Data? Does the thought of an aggregation pipeline scare you? Come and see this talk to learn about the various tools available to running aggregations and building visualisations on MongoDB Data, including a sneak preview of our upcoming Charts product.
Webinar: MongoDB and Analytics: Building Solutions with the MongoDB BI ConnectorMongoDB
MongoDB is known for being a developers database of choice, but what about data analysts? MongoDB 3.2 has introduced the MongoDB BI Connector – to allow users to connect to an instance using their analytics tool of choice. Now users of Tableau, QlikView, Excel, Cognos, and countless others can connect to MongoDB and immediately begin building reporting solutions. In this webinar, we will cover the architecture needed to use the BI Connector with MongoDB. We will also demonstrate how to build reports with your data.
[MongoDB.local Bengaluru 2018] Jumpstart: Introduction to Schema DesignMongoDB
Presented by: Saurabh Kashikar
Abstract: MongoDB’s basic unit of storage is a document. Documents can represent rich, schema-free data structures, meaning that we have several viable alternatives to the normalized, relational model. If you are new to MongoDB, learn the schema design basics in this introductory session. This session will help you model basic relationships in MongoDB.
What You Will Learn:
- The fundamentals of the MongoDB document model.
- How to model 1-1 and one-to-many (1-N) relationships in MongoDB.
- How to model many-to-many (N-N) relationships in MongoDB.
[MongoDB.local Bengaluru 2018] The Path to Truly Understanding Your MongoDB DataMongoDB
Presented by: Vivek Singh
Abstract: Do you want to run analytics on your MongoDB Data? Does the thought of an aggregation pipeline scare you? Come and see this talk to learn about the various tools available to running aggregations and building visualisations on MongoDB Data, including a sneak preview of our upcoming Charts product.
Webinar: MongoDB and Analytics: Building Solutions with the MongoDB BI ConnectorMongoDB
MongoDB is known for being a developers database of choice, but what about data analysts? MongoDB 3.2 has introduced the MongoDB BI Connector – to allow users to connect to an instance using their analytics tool of choice. Now users of Tableau, QlikView, Excel, Cognos, and countless others can connect to MongoDB and immediately begin building reporting solutions. In this webinar, we will cover the architecture needed to use the BI Connector with MongoDB. We will also demonstrate how to build reports with your data.
MongoDB .local Paris 2020: Les bonnes pratiques pour travailler avec les donn...MongoDB
Les données de séries chronologiques sont de plus en plus au cœur des applications modernes: pensez à l'IoT, aux transactions sur actions, aux flux de clics, aux médias sociaux, etc. Avec le passage des systèmes batch aux systèmes temps réel, la capture et l'analyse efficaces des données de séries chronologiques peuvent permettre aux entreprises de mieux détecter et réagir aux événements en avance sur leurs concurrents ou d'améliorer l'efficacité opérationnelle pour réduire les coûts et les risques. Travailler avec des données de séries chronologiques est souvent différent des données d’application classiques et vous devez observer les meilleures pratiques. Cette conférence couvre: Composants communs d'une solution IoT Les défis liés à la gestion de données chronologiques dans les applications IoT Différentes conceptions de schéma et leur incidence sur l'utilisation de la mémoire et du disque sont deux facteurs déterminants dans les performances des applications. Comment interroger, analyser et présenter les données de séries chronologiques IoT à l'aide de MongoDB Compass et MongoDB Charts À la fin de la session, vous aurez une meilleure compréhension des meilleures pratiques clés en matière de gestion des données de séries chronologiques de l'IoT avec MongoDB.
MongoDB .local Chicago 2019: Using MongoDB Transactions to Implement Cryptogr...MongoDB
Have you ever wondered whether a blockchain (permissioned or permissionless) which distributes data among multiple participants is right for your use cases? Perhaps, what you really wanted is an information store that maintains change history of information with cryptographic verification? If so, then this session is for you.
In this talk, we will demonstrate how to build a cryptographically verifiable change history using MongoDB. Using existing MongoDB constructs such as Transactions, we will show a developer-friendly library that can support ledger functionality such as insert, update, and verify while preserving the MongoDB query semantics. We will then discuss Ledger use cases for a variety of applications.
Webinar: Introducing the MongoDB Connector for BI 2.0 with TableauMongoDB
Pairing your real-time operational data stored in a modern database like MongoDB with first-class business intelligence platforms like Tableau enables new insights to be discovered faster than ever before.
Many leading organizations already use MongoDB in conjunction with Tableau including a top American investment bank and the world’s largest airline. With the Connector for BI 2.0, it’s never been easier to streamline the connection process between these two systems.
In this webinar, we will create a live connection from Tableau Desktop to a MongoDB cluster using the Connector for BI. Once we have Tableau Desktop and MongoDB connected, we will demonstrate the visual power of Tableau to explore the agile data storage of MongoDB.
You’ll walk away knowing:
- How to configure MongoDB with Tableau using the updated connector
- Best practices for working with documents in a BI environment
- How leading companies are using big data visualization strategies to transform their businesses
MongoDB .local Chicago 2019: MongoDB – Powering the new age data demandsMongoDB
To successfully implement our clients' unique use cases and data patterns, it is mandatory that we unlearn many relational concepts while designing and rapidly developing efficient applications in NoSQL.
In this session, we will talk about some of our client use cases and the strategies we adopted using features of MongoDB.
Beyond the Basics 3: Introduction to the MongoDB BI ConnectorMongoDB
Watch this presentation to learn how the MongoDB BI Connector lets you use MongoDB as a data source for your SQL-based BI and analytics platforms.
Learn how to seamlessly create the visualizations and dashboards that will help you extract the insights and hidden value in your multi-structured data.
MongoDB .local Paris 2020: Devenez explorateur de données avec MongoDB ChartsMongoDB
De nos jours, tout le monde devrait être "Data Analyst". Mais avec tant de données disponibles, comment les comprendre et vous assurer que vous prenez les meilleures décisions ? Une excellente approche consiste à utiliser des visualisations de données. Au cours de cette présentation, notre expert utilisera un jeu de données complexe et vous montrera comment l'étendue des fonctionnalités de MongoDB Charts peut vous aider à transformer les bits et bytes en informations.
MongoDB .local Munich 2019: A Complete Methodology to 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.
Business Jumpstart: The Right (and Wrong) Use Cases for MongoDBMongoDB
New to MongoDB? This talk will cover when to use MongoDB and how to evaluate if MongoDB is a fit for your project. You will see how MongoDB's flexible document model is solving business problems in ways that were not previously possible, and how MongoDB's built-in features allow running at scale. No prior knowledge of MongoDB is assumed.
Webinar: How Financial Firms Create a Single Customer View with MongoDBMongoDB
Learn why a tier 1 bank, top 5 insurance provider and other global financial services companies are flocking to MongoDB. This webinar focuses on how firms use MongoDB to generate a single customer view not only to comply with KYC and other regulations, but also to engage customers efficiently, which helps reduce churn and increase wallet share while still reducing costs. We will focus on how MongoDB's dynamic schema, real-time replication and auto-scaling make it possible to create a global, unified data hub aggregating disparate data sources, which can be made available to customers, customer service representatives (CSRs), and relationship managers (RMs).
Webinar: Elevate Your Enterprise Architecture with In-Memory ComputingMongoDB
The advantages of in-memory computing are well understood. Data can be accessed in RAM nearly 100,000 times faster than retrieving it from disk, delivering orders-of-magnitude higher performance for the most demanding applications. Examples include real-time re-scoring of personalized product recommendations as users are browsing a site, or trading stocks in immediate response to market events.
In this webinar, we’ll briefly explore the trends driving in-memory computing (IMC), the challenges that surround it, and how MongoDB fits into the big picture.
Topics covered in this session will include:
- IMC use cases and customer case studies
- Critical capabilities and components of IMC
- How MongoDB plays a role in an overall IMC strategy within your enterprise architecture
- Suggested architectures related to MongoDB’s in-memory capabilities:
-- Integration with Apache Spark
-- In-Memory Storage Engine
-- Integration with BI tools
MongoDB and RDBMS: Using Polyglot Persistence at Equifax MongoDB
MongoDB and RDBMS: Using Polyglot Persistence at Equifax. Presented by Michael Lawrence, Pariveda Solutions on behalf of Equifax at MongoDB Evenings Atlanta on September 24, 2015.
During this presentation, Infusion and MongoDB shared their mainframe optimization experiences and best practices. These have been gained from working with a variety of organizations, including a case study from one of the world’s largest banks. MongoDB and Infusion bring a tested approach that provides a new way of modernizing mainframe applications, while keeping pace with the demand for new digital services.
Mobility: It's Time to Be Available for HERMongoDB
In order to meet the needs of the digitally-oriented consumer, retailers need to offer personalized service in real-time. By embracing mobile to deliver an integrated experience to customers, retailers can open new business opportunities.
Yet, for many traditional retailers, providing a seamless experience across mobile and other channels presents challenges due to the limitations of legacy technology infrastructure and the ability to act in ‘real-time’. However, a new class of database technology is emerging that enables retailers to support new business requirements, improve customer experience and reduce cost. In the next session of webinar series - Omni-Channel Retailing: One-Step-at a Time you will learn why more and more retailers and ecommerce players are turning to MongoDB as a choice for their mobile platforms. Based on existing customers you will learn:
How to meet the consumer where she is, whenever she wants - know where she is using geo-spatial services
Engage with her and provide a ‘real-time’ experience, tailored to her expectations - check-her in or ‘check-her out’ at the POS and provide the latest update
Deliver the most up-to-date information to your associates so they are empowered to serve the consumer when she engages with your brand - deliver the latest inventory information via mobile app to your employee
In this discussion, you learn the latest in business techniques and how you can take advantage of MongoDB to deliver another piece of Omni-channel imperative - meeting your customer - at her convenience.
MongoDB .local Paris 2020: Les bonnes pratiques pour travailler avec les donn...MongoDB
Les données de séries chronologiques sont de plus en plus au cœur des applications modernes: pensez à l'IoT, aux transactions sur actions, aux flux de clics, aux médias sociaux, etc. Avec le passage des systèmes batch aux systèmes temps réel, la capture et l'analyse efficaces des données de séries chronologiques peuvent permettre aux entreprises de mieux détecter et réagir aux événements en avance sur leurs concurrents ou d'améliorer l'efficacité opérationnelle pour réduire les coûts et les risques. Travailler avec des données de séries chronologiques est souvent différent des données d’application classiques et vous devez observer les meilleures pratiques. Cette conférence couvre: Composants communs d'une solution IoT Les défis liés à la gestion de données chronologiques dans les applications IoT Différentes conceptions de schéma et leur incidence sur l'utilisation de la mémoire et du disque sont deux facteurs déterminants dans les performances des applications. Comment interroger, analyser et présenter les données de séries chronologiques IoT à l'aide de MongoDB Compass et MongoDB Charts À la fin de la session, vous aurez une meilleure compréhension des meilleures pratiques clés en matière de gestion des données de séries chronologiques de l'IoT avec MongoDB.
MongoDB .local Chicago 2019: Using MongoDB Transactions to Implement Cryptogr...MongoDB
Have you ever wondered whether a blockchain (permissioned or permissionless) which distributes data among multiple participants is right for your use cases? Perhaps, what you really wanted is an information store that maintains change history of information with cryptographic verification? If so, then this session is for you.
In this talk, we will demonstrate how to build a cryptographically verifiable change history using MongoDB. Using existing MongoDB constructs such as Transactions, we will show a developer-friendly library that can support ledger functionality such as insert, update, and verify while preserving the MongoDB query semantics. We will then discuss Ledger use cases for a variety of applications.
Webinar: Introducing the MongoDB Connector for BI 2.0 with TableauMongoDB
Pairing your real-time operational data stored in a modern database like MongoDB with first-class business intelligence platforms like Tableau enables new insights to be discovered faster than ever before.
Many leading organizations already use MongoDB in conjunction with Tableau including a top American investment bank and the world’s largest airline. With the Connector for BI 2.0, it’s never been easier to streamline the connection process between these two systems.
In this webinar, we will create a live connection from Tableau Desktop to a MongoDB cluster using the Connector for BI. Once we have Tableau Desktop and MongoDB connected, we will demonstrate the visual power of Tableau to explore the agile data storage of MongoDB.
You’ll walk away knowing:
- How to configure MongoDB with Tableau using the updated connector
- Best practices for working with documents in a BI environment
- How leading companies are using big data visualization strategies to transform their businesses
MongoDB .local Chicago 2019: MongoDB – Powering the new age data demandsMongoDB
To successfully implement our clients' unique use cases and data patterns, it is mandatory that we unlearn many relational concepts while designing and rapidly developing efficient applications in NoSQL.
In this session, we will talk about some of our client use cases and the strategies we adopted using features of MongoDB.
Beyond the Basics 3: Introduction to the MongoDB BI ConnectorMongoDB
Watch this presentation to learn how the MongoDB BI Connector lets you use MongoDB as a data source for your SQL-based BI and analytics platforms.
Learn how to seamlessly create the visualizations and dashboards that will help you extract the insights and hidden value in your multi-structured data.
MongoDB .local Paris 2020: Devenez explorateur de données avec MongoDB ChartsMongoDB
De nos jours, tout le monde devrait être "Data Analyst". Mais avec tant de données disponibles, comment les comprendre et vous assurer que vous prenez les meilleures décisions ? Une excellente approche consiste à utiliser des visualisations de données. Au cours de cette présentation, notre expert utilisera un jeu de données complexe et vous montrera comment l'étendue des fonctionnalités de MongoDB Charts peut vous aider à transformer les bits et bytes en informations.
MongoDB .local Munich 2019: A Complete Methodology to 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.
Business Jumpstart: The Right (and Wrong) Use Cases for MongoDBMongoDB
New to MongoDB? This talk will cover when to use MongoDB and how to evaluate if MongoDB is a fit for your project. You will see how MongoDB's flexible document model is solving business problems in ways that were not previously possible, and how MongoDB's built-in features allow running at scale. No prior knowledge of MongoDB is assumed.
Webinar: How Financial Firms Create a Single Customer View with MongoDBMongoDB
Learn why a tier 1 bank, top 5 insurance provider and other global financial services companies are flocking to MongoDB. This webinar focuses on how firms use MongoDB to generate a single customer view not only to comply with KYC and other regulations, but also to engage customers efficiently, which helps reduce churn and increase wallet share while still reducing costs. We will focus on how MongoDB's dynamic schema, real-time replication and auto-scaling make it possible to create a global, unified data hub aggregating disparate data sources, which can be made available to customers, customer service representatives (CSRs), and relationship managers (RMs).
Webinar: Elevate Your Enterprise Architecture with In-Memory ComputingMongoDB
The advantages of in-memory computing are well understood. Data can be accessed in RAM nearly 100,000 times faster than retrieving it from disk, delivering orders-of-magnitude higher performance for the most demanding applications. Examples include real-time re-scoring of personalized product recommendations as users are browsing a site, or trading stocks in immediate response to market events.
In this webinar, we’ll briefly explore the trends driving in-memory computing (IMC), the challenges that surround it, and how MongoDB fits into the big picture.
Topics covered in this session will include:
- IMC use cases and customer case studies
- Critical capabilities and components of IMC
- How MongoDB plays a role in an overall IMC strategy within your enterprise architecture
- Suggested architectures related to MongoDB’s in-memory capabilities:
-- Integration with Apache Spark
-- In-Memory Storage Engine
-- Integration with BI tools
MongoDB and RDBMS: Using Polyglot Persistence at Equifax MongoDB
MongoDB and RDBMS: Using Polyglot Persistence at Equifax. Presented by Michael Lawrence, Pariveda Solutions on behalf of Equifax at MongoDB Evenings Atlanta on September 24, 2015.
During this presentation, Infusion and MongoDB shared their mainframe optimization experiences and best practices. These have been gained from working with a variety of organizations, including a case study from one of the world’s largest banks. MongoDB and Infusion bring a tested approach that provides a new way of modernizing mainframe applications, while keeping pace with the demand for new digital services.
Mobility: It's Time to Be Available for HERMongoDB
In order to meet the needs of the digitally-oriented consumer, retailers need to offer personalized service in real-time. By embracing mobile to deliver an integrated experience to customers, retailers can open new business opportunities.
Yet, for many traditional retailers, providing a seamless experience across mobile and other channels presents challenges due to the limitations of legacy technology infrastructure and the ability to act in ‘real-time’. However, a new class of database technology is emerging that enables retailers to support new business requirements, improve customer experience and reduce cost. In the next session of webinar series - Omni-Channel Retailing: One-Step-at a Time you will learn why more and more retailers and ecommerce players are turning to MongoDB as a choice for their mobile platforms. Based on existing customers you will learn:
How to meet the consumer where she is, whenever she wants - know where she is using geo-spatial services
Engage with her and provide a ‘real-time’ experience, tailored to her expectations - check-her in or ‘check-her out’ at the POS and provide the latest update
Deliver the most up-to-date information to your associates so they are empowered to serve the consumer when she engages with your brand - deliver the latest inventory information via mobile app to your employee
In this discussion, you learn the latest in business techniques and how you can take advantage of MongoDB to deliver another piece of Omni-channel imperative - meeting your customer - at her convenience.
Schnellere Digitalisierung mit einer cloudbasierten DatenstrategieMongoDB
Am 5. Juli zeigen wir Ihnen in Düsseldorf anhand unserer Best Practices für die Ausarbeitung und Optimierung einer cloudbasierten Datenstrategie, wie Sie die digitale Transformation in Ihrem Unternehmen beschleunigen können.
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.
Enabling Telco to Build and Run Modern Applications Tugdual Grall
See how new databases like MongoDB enable Telco Enterprises to Build and Run Modern Applications.
This presentations was delivered in Tel Aviv in Jan-2015 during a Telco round table organized by Matrix.
This is a quick overview of the challenges that BigData and Flexible Schema Databases like MongoDB offer regarding Data Treatment and strategies to overcome them.
Unlocking Operational Intelligence from the Data LakeMongoDB
Hadoop-based data lakes are enabling enterprises and governments to efficiently capture and analyze unprecedented volumes of data. Join this webinar to learn how digital transformation is driving the rise of the data lake, the role Hadoop plays in generating new classes of analytics and insight, the critical capabilities you need to evaluate in an operational database for your data lake, and more.
Cloud Modernization and Data as a Service OptionDenodo
Watch: https://bit.ly/2E99UNO
The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms. Cloud has become a key component of modern architecture design. Data lakes, IoT, NoSQL, SaaS, etc. coexist with relational databases to fuel the needs of modern analytics, ML and AI. Exploring and understanding the data available within your organization is a time-consuming task. And all of this without even knowing if that data will be useful at all.
Attend this session to learn:
- How dynamic data challenges and the speed of change requires a new approach to data architecture.
- Learn how logical data architecture can enable organizations to transition data faster to the cloud with zero downtime.
- Explore how data as a service and other API management capabilities is a must in a hybrid cloud environment.
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
OPEN'17_4_Postgres: The Centerpiece for Modernising IT InfrastructuresKangaroot
Postgres is the leading open source database management system that is being developed by a very active community for more than 15 years. Gaby Schilders is Sales Engineer at EnterpriseDB, supplier of the EDB Postgres data platform.
Gaby Schilders, Sales Engineer at EnterpriseDB, will be explaining why companies take open source as the centerpiece for modernising their IT infrastructure, thus increasing their scalability and taking full advantage today's technologies offer them.
Data Streaming with Apache Kafka & MongoDBconfluent
Explore the use-cases and architecture for Apache Kafka, and how it integrates with MongoDB to build sophisticated data-driven applications that exploit new sources of data.
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.
Similar to Accelerating a Path to Digital With a Cloud Data Strategy (20)
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
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https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
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Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
3. 3
SPEAKERS
Accelerating a Path to Digital with a Cloud Data Strategy
MAT KEEP
BART VAN LOOCKE
DIRECTOR OF PRODUCT
MONGODB
SALES DIRECTOR
INFOSYS LIMITED
SOFTWARE ENGINEER
DE PERSGROEP
SENIOR SOLUTIONS ARCHITECT
MONGODB
EUGENE BOGAART
PRAVEEN BISHT
SACHA VANSIMPSEN
FREDERIC BOTHY
TOYOTA MOTOR EUROPE
MONGODB
SENIOR ACCOUNT EXECUTIVE
SYSTEMS ENGINEER
4. • Welcome
• Executing on a Cloud Data Strategy
• Customer Story: De Persgroep
• Break
• Customer Story:Toyota Motor Europe &
Infosys Limited
• Landing in the Cloud
• Q&A& Lunch
Agenda
5. EXECUTING ON A CLOUD DATA STRATEGY
Mat Keep, Director, Product Team
mat.keep@mongodb.com
@matkeep
6. Mainframe Client-Server Web
Control & Efficiency AGILITY & INNOVATION
Cloud & Mobile
Distributed Systems
1980s Late 90s – 2000s 2015>1960s-70s
The Cloud Age
Generational Shift
9. Why do I need to rethink my underlying data layer…..?
Support the velocity of
modern app development
Exploit commodity &
cloud platforms
Deploy anywhere, on-
demand, with no lock-in
10. API Access Layer
Operational Data
Customers
Products
Accounts
ML Models
Shared Physical Infrastructure
App1 App2 App3
1.Development agility
2.Corporate governance
3.Data re-use
Cloud Data Strategy
Standardized, on-demand database service
Cloud Portable
Any Cloud, Any Where
11. Best way to
work with data
Intelligently put data
where you need it
Freedom
to run anywhere
Intelligent Operational Data PlatformIntelligent Operational Data PlatformIntelligent Operational Data PlatformIntelligent Operational Data PlatformIntelligent Operational Data Platform
Why MongoDB?
12. Freedom To Run Anywhere
Database that runs
the same everywhere
Coverage in any
geography
Leverage the benefits
of a multi-cloud
strategy
Avoid lock-in
Mainframe
Database as a service
ServerLaptop Self-managed in the cloud
15. MongoDB Ops Manager
Management Platform For Private DBaas
Monitoring
• Deploy, resize,
and upgrade
your
deployments
with just a few
clicks
• RESTful API to
integrate with
your enterprise
orchestration
tools
• Allocate and
create pre-
provisioned
server pools;
Cloud Foundry
Integration
Automation Backup
• Continuous
backups to
minimize your
exposure to data
loss
• Restore to
precisely the
moment you
need with point-
in-time recovery
• Dozens of charts
tracking key
performance
indicators
• Custom alerts
that trigger when
key metrics are
out of range
• RESTful API to
integrate with
your existing
APM tools
16. From Traditional To DBaaS
• Slow to build and launch
new applications
• Multiple copies of data
• Complex data
reconciliation controls
• High licensing costs
• Sprawling server estate
12,000+ RDBMS Instances
3,500 Systems, 40,000 Cores
1,200+ Coherence Instances
17. Data Fabric
Multi-tenant PaaS
Exposing APIs for data streaming and
storage
Cloud native, self-service
Modern, industry standard, open source
technologies
Intra-day releases
Multi-data center
“Data Fabric provides data storage, query and distribution as
a service, enabling application developers to concentrate on
business functionality.”
Data Fabric Clients
Java, .NET, REST
API Layer
CRUD & Streaming
App Server Layer
Java + Linux
Database
MongoDB
Messaging
Kakfa
Security
Authentication&Audit
Data Fabric
18. Results
• £m license cost avoidance (Coherence)
• Plans to decommission hundreds of servers
• Coherence
• Oracle/SQL Server databases
Cost
Reduction
• 2 foundational applications refactored off
Coherence
• Supporting data needs of a dozen applications
Simplification
• Velocity: Develop new applications in days
• No need for database administration
• self-service data service
• Promotes collaboration and data sharing
Velocity
Slide taken from https://www.mongodb.com/presentations/mongodb-days-uk-building-an-enterprise-data-fabric-at-royal-bank-of-scotland-with-mongodb
20. 20
You have 2 choices: Self-Managed or DBaaS
Cloud Migration
or Cloud First
Self-Managed
Aka “Lift and Shift”
Database as
a service
Fork in
the road
21. 21
You have 2 choices: Self-Managed or DBaaS
Cloud Migration
or Cloud First
Self-Managed
Aka “Lift and Shift”
Database as
a service
Fork in
the road
1. Provision instances and storage
2. Configure HA
3. Configure security
4. Configure backup/restore
5. Monitoring & alerting
6. Ongoing upgrades & maintenance
22. 22
You have 2 choices: Self-Managed or DBaaS
Cloud Migration
or Cloud First
Self-Managed
Aka “Lift and Shift”
Database as
a service
Fork in
the road
1. Provision instances and storage
2. Configure HA
3. Configure security
4. Configure backup/restore
5. Monitoring & alerting
6. Ongoing upgrades & maintenance
Choose instance, hit deploy,
wait a couple of minutes
24. 24
MongoDB Atlas unlocks agility & reduces cost
Self-service, elastic,
and automated
Global and highly
available
Secure by default
Comprehensive
monitoring
Managed disaster
recovery
Cloud agnostic
25. MongoDB Atlas Powering
Microservices Architecture
Problem Why MongoDB ResultsProblem Solution Results
Over 35 different apps accessed by
10,000+ unique customers on AWS
Each experiment produces millions of
“rows” of data, which led to suboptimal
performance with incumbent databases
RDS & Aurora slow, added code
complexity
DynamoDB limited query functionality &
expensive
MongoDB Atlas managed database
service
Flexible document model allows
storage of multi-structured data
Expressive query language and
secondary indexes allow ad-hoc
analysis of experiment data
Scalability to handle growing data
volumes
Thermo Fisher customers now obtain
real-time insights from mass
spectrometry experiments from any
mobile device or browser; not possible
before
Improved developer productivity with
40x less code, improved performance
by 6x
Easy migration process & zero
downtime. Testing to production in
under 2 months
27. Conclusion
1 Cloud is more than just a new
platform: microservices, agile,
DevOps enable new ways of
delivering apps faster
2 Cloud data strategy is an
essential building block
3 MongoDB is the foundation for
cloud data
28. Resources To Get Started
Spin up a cluster on the
Free Tier today
Download the Whitepaper
30. SAFE HARBOUR STATEMENT
This presentation contains “forward-looking statements” within the meaning of Section 27A of the
Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as
amended. Such forward-looking statements are subject to a number of risks, uncertainties, assumptions
and other factors that could cause actual results and the timing of certain events to differ materially from
future results expressed or implied by the forward-looking statements. Factors that could cause or
contribute to such differences include, but are not limited to, those identified our filings with the
Securities and Exchange Commission. You should not rely upon forward-looking statements as
predictions of future events. Furthermore, such forward-looking statements speak only as of the date of
this presentation.
In particular, the development, release, and timing of any features or functionality described for
MongoDB products remains at MongoDB’s sole discretion. This information is merely intended to
outline our general product direction and it should not be relied on in making a purchasing decision nor
is this a commitment, promise or legal obligation to deliver any material, code, or functionality. Except
as required by law, we undertake no obligation to update any forward-looking statements to reflect
events or circumstances after the date of such statements.
31. MongoDB: Already Used Across Every Industry and
Use Case...
eCommerce
Travel Graph &
Recommendation System
Analytics
Internet of Things
Product Catalog
Artificial Intelligence
Digital Transformation
Drug Sequencing
Gaming
Single View
Mobile
Database as a Service
...without multi-document ACID transactions
32. Relational Database
Related data split across multiple records and tables.
Multi-record transactions essential
Different databases take different approaches
Document Database
Related data contained in a single, rich document.
Transaction scoped to the document
Data Models and Transactions
33. Just like relational transactions
● Multi-statement, familiar relational syntax
● Easy to add to any application
● Multiple documents in 1 or many collections
ACID guarantees
● Snapshot isolation, all or nothing execution
● No performance impact for non-transactional
operations
Schedule
● MongoDB 4.0, Summer ‘18: replica set
● MongoDB 4.2: extended to sharded clusters
MongoDB Multi-Document Transactions
34. Major engineering investment over 3+ years touching every part of
the server and drivers
● Storage layer
● Replication consensus protocol
● Sharding architecture
● Consistency and durability guarantees
● Global logical clock
● Cluster metadata management
● Exposed to drivers through API enhancements
We’re 85% done…...
Our Journey to Acid Transactions
35. SUMMARY: MongoDB UNIQUELY Delivers…...
Scale-out, data locality, and
resilience of distributed systems
ACID transactional guarantees
of relational databases
Developer productivity
of document databases
Freedom to Run Anywhere
44. Autonomous Squad
➔ Small, co-located, self organised
➔ End-to-end responsibility for the stuff
they build, from design to
maintenance.
➔ Within the scope of its mission, a
squad is empowered to decide what to
build, how to build it and how to work
together while doing it.
58. 58
On Premise MongoDB
▪ MongoDB 2.6
▪ 1200GB
▪ 85 Databases
▪ MongoDB 3.2
▪ < 50GB
▪ 80 Databases
Upgrade was imposible: too many squads/applications involved!
▪ ...
59. 59
MongoDB 2.6 on-premise > Cloud
Problem:
no migration tools available (in 2017)
Some different strategies:
➔ copy data
➔ duplicate data
➔ incremental update
➔ ..
60. 60
Copy data @deploy time
DB 1
Application
DB 1
Application
DB 2
DB 2
Application
copy data
Small applications with downtime
61. 61
Duplicate data @runtime
DB 1
Application
DB 1
Application
DB 2
DB 2
Application
Applications with mostly CREATE actions
62. 62
Incremental update @deploy time
DB 1
Application
DB 1
Application
DB 2
DB 2
Application
Applications with mostly UPDATE actions
DB 2
copy data
{migrated : ‘N’}
migrate
d
Y
migrate
d
Y
66. 66
Isolation
Originally the goal was to have a cluster / application / environment.
However this is not a feasible strategy > high costs
DEV/TEST/ACC
APP A APP B APP C
DEVTESTACC
APP A APP B APP C
APP A APP B APP C
Cluster
PROD
APP A APP B APP C
PROD
Cluster
2 Clusters per domain (non-prod and prod)
67. 67
CPU Steal
M10 and M20 instances are running on t2-family machines (AWS)
Example: M10 > t2.small > 12 credits/hour > 20%
75. TOYOTA MOTOR EUROPE AND INFOSYS
30th May 2018
75
An example case of leveraging MongoDB Atlas to deliver high quality,
predictable and scalable database services..
76. TOYOTA IN EUROPE
• Began selling cars in 1963
• 9 manufacturing plants in 7countries
• Network of 30National Marketing and Sales Companies in 53 countries.
• Network of over 3000Toyota and Lexus authorised retailers.
• Directly employ over 20,000people across Europe.
• In 2017 sold 1,001,700vehicles in Europe
• 45%of Toyota Motor Europe (TME) sales in 2018-Q1 are hybrid electric vehicles
77. INFOSYS IS A ‘$10BN+’ GLOBAL, SCALABLE AND DIVERSE
ORGANIZATION WITH ‘200,000+ EMPLOYEES’ AND ‘1,200+ CLIENTS IN
45 COUNTRIES’..
77
• 97.6% of our revenues come
from existing customers
• Shared business vision and
commercial objectives
• 97% of our projects are delivered in
time and to budget
Customers
are the anchor for
everything we do, and the
metric of our success
Predictability
helps our customers achieve
programme objectives in time
and within budget
• Investment in purposeful AI based platforms to
drive automation
• Innovation to deliver change through DT and
ZD
Innovation
$500 million innovation
fund
78. INFOSYS RELATIONSHIP WITH TOYOTA
78
Toyota Motor North America - Since 2007
Toyota Motor Europe- Since 2009
Toyota Kirloskar Motor , India – Since 2008
Toyota Financial Services - Since 2010
Toyota Great Britain - Since 2013
Toyota Financial Services, UK - Since Jan 2017
Toyota Sweden - Since 2016
Long term strategic partnership with global overview across 3 continents
A multi-discipline, multi geography relationship which has matured over the last nine years from a
projects based engagement to a strategic partnership across Europe, North America and Asia
Toyota Connected - Since 2016
Toyota Motor Manufacturing France - Since 2016
79. MONGODB FOOTPRINT IN TOYOTA MOTOR EUROPE
79
15+ B2B & B2C Applications
45 Toyota Websites
39 Lexus Websites
50+ Environments
80. HOW DID WE END UP WITH MONGODB ATLAS
80
1. Features
2. Support
3. Cost
4. Migration Effort
Evaluation criteria
81. ATLAS MIGRATION – OUR APPROACH
Mongodb 2.6 cluster on mlabs
Upgrade in-place
from 2.6 to 3.0
on mlabs
Mongodb 3.0 cluster on
mlabs/Heroku
Option 1 - Migrate from mlabs 3.0 to
Atlas 3.2 (using MongoMirror)
Mongodb 3.2 cluster on Atlas
Application remediation/testing for upgrade
to 3.0
1 2
• Switch DB connections to Atlas clusters
• Application testing for upgrade to 3.2
Option 2 – Export data files from mlabs 3.0 to temp env and
import to Atlas 3.2
82. MONGODB ROLE IN CURRENT TOYOTA MOTOR EUROPE CLOUD
ECOSYSTEM
Microservice
Microservice
Microservice
Microservice
Microservice
Microservice
Microservice
MicroserviceKafka
Connectors
Schema
Registry
Microservice
Microservice
Microservice
Microservice
Public Cloud 1 Public Cloud 2
84. LANDING IN THE CLOUD
MIGRATING FROM RELATIONAL, ON PREMISES TO MONGODB IN THE CLOUD
Eugene Bogaart, Senior Solutions Architect
eugene@mongodb.com
85. LANDING IN THE CLOUD
Migrating from Relational, On Premises, to MongoDB in the Cloud.
86. DATA MODELS DIFFERENCES
Relational Database
Related data split across multiple records and tables.
Multi-record transactions essential
Different databases take different approaches
Document Database
Related data contained in a single, rich document.
Transaction scoped to the document
87. RECIPE: STEP 1
• Design Data Model,
○ New Model, requires understanding of the data
○ Application Impact, simplify data access and ORM
88. 88
Developer like ORM's
Thousands
of lines of
configuration code….
Total pain in the...
Customer
Opportunit
y
Contact
ARR Address Contact Roles
Opportunity
Team
Phone Phone
Objects
Tables
Lead
NameName
Activity
History
Open
Activities
Customer
Detail
Summary
Object Relational Mapping Layer...which needs to be
updated whenever
the schema
changes
89. 89
With MongoDB, without ORM
Customer
Customer
Opportunity
Opportunity
Contact
Contact
Lead
Lead
Objects
Database
91. CONVERT DATA
Relational Database
Related data split across multiple records and tables.
Multi-record transactions essential
Different databases take different approaches
Document Database
Related data contained in a single, rich document.
Transaction scoped to the document
92. RECIPE: STEP 2
• Design Data Model,
○ New Model, requires understanding of the data
○ Application Impact, simplify data access and ORM
• Convert Data
○ Bulk, merge data in new model
○ Change Data Capture, if large dataset involved which
cannot be offline
○ Custom, opportunity to do some data cleansing
93. HOW TO GET INTO THE CLOUD?
Cloud Migration
or Cloud First
Self-Managed
Aka “Lift and Shift”
Database as
a service
Fork in
the road
1. Provision instances and storage
2. Configure HA
3. Configure security
4. Configure backup/restore
5. Monitoring & alerting
6. Ongoing upgrades & maintenance
Choose instance, hit deploy,
wait a couple of minutes
“You have 2 Choices…”
94. HOW TO GET INTO MONGODB ATLAS?
Migrate existing deployments running
anywhere into MongoDB Atlas with minimal
impact to your application. Live migration
works by:
● Performing a sync between your source
database and a target database hosted in
MongoDB Atlas
● Syncing live data between your source
database and the target database by
tailing the oplog
● Notifying you when its time to cut over to
the MongoDB Atlas cluster
Live Migration
95. RECIPE: STEP 3
• Migrate data to Cloud,
○ MongoDB Altas Live Migration
■ Wizard run from destination
○ MongoDB Mirror
■ Run from source
96.
97. DEMO CONTEXT
Existing Database in Tabular database with employee information.
Contains, past and present information with managers, departments, titles and salary.
Main application is a for managers who can view who reports to them
And view company history of their direct (and indirect) reports.
98. ○ New Data Model
○ Convert Data
○ Altas Live Migration
DEMO SETUP
100. ○ New Data Model
○ Convert Data
○ Altas Live Migration
WRAP UP DEMO
101. LANDING IN THE CLOUD
• Design Data Model -> shift in paradigm
• Convert you data -> some manual work
• Migrate to MongoDB Atlas -> tooling provided
102. SUMMARY: MONGODB UNIQUELY DELIVERS…...
Scale-out, data locality, and
resilience of distributed systems
ACID transactional guarantees
of relational databases
Developer productivity
of document databases
Freedom to Run Anywhere
106. MONGODB CONNECTOR FOR BI
• Run analytical queries on live
MongoDB data
• Can run against your primary or
secondaries
• Runs on any server, or co-locate with
your database process for optimal
performance
108. All MongoDB Atlas nodes are single-tenant and
deployed into their own VPC for security isolation.
In-flight security:
● TLS/SSL for in-flight data encryption
● Authentication and authorization access controls
with SCRAM-SHA1
● IP whitelists
At-rest security:
● Encrypted storage volumes
● AES-256 (CBC mode) hardware encryption with
Seagate Self-Encrypting Drives
Under the hood
SECURE IN THE CLOUD
110. Under the hood
Out-of-the-Box Operational Tooling
● Fine Grained Monitoring and Alerts
● Real-Time Performance Panel
● Data Explorer
● Query/Performance Optimization
● Continuous Backup/Point-in-Time
Restore
● Query-able Backup
● Enterprise APM Integration
● Programmatic API Management
111. Highly Available by Default
Under the hood
● A minimum of three data nodes per
replica set/shard are automatically
deployed across availability zones for
high availability
● If your primary node does go down for
any reason, the self healing recovery
process in MongoDB Atlas will typically
occur in under 2 seconds
112. The Latest MongoDB Features
Under the hood
● MongoDB Atlas comes out-of-the-box with
MongoDB 3.2 and MongoDB 3.4 available. When
maintenance releases become available, MongoDB
Atlas will automatically upgrade your cluster, using a
rolling process to maintain cluster availability at all
times
● When new versions of MongoDB are released,
MongoDB Atlas will also allow you to make
seamless upgrades without risking downtime
114. ELASTIC SCALABILITY & ON-DEMAND
PROVISIONING
Under the hood
● WiredTiger storage engine with compression and fine-
grained concurrency control to meet the most demanding
SLAs
● MongoDB Atlas supports automatic-sharding, giving you the
ability to scale up or out with no impact to your app
● MongoDB Atlas allows you to pick the shard key that best
suits your application needs
● All MongoDB Atlas clusters are single-tenant and deployed
on servers allocated specifically to the cluster
116. Integrated services and
functions for complex,
multi-stage workflows
Native SDKs for
Android, JS, and iOS
apps
Direct Database
Access
MongoDB Stitch