Webinar: An Enterprise Architect’s View of MongoDBMongoDB
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
MongoDB is more than just a great application database for developers; it gives Enterprise Architects new capabilities to solve previously difficult architectural requirements much more easily. Take for example the challenge of many siloed systems at MetLife – with MongoDB, the Metlife team was able to successfully provide a single view into those 70 systems, in only 3 months.
In this webinar, we will:
Explore real life challenges enterprises face with case studies of their solutions
Consider how best to introduce MongoDB in the enterprise
Give an overview of how to optimize the use of MongoDB
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.
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.
Join CIGNEX Datamatics, Alfresco’s Global Platinum Partner, as they share the case study experience of a leading global online university. Together we’ll take a close look at their document management and web portal solution and their integrations with Alfresco ECM, Liferay Portal and Moodle Learning Management System.
Webinar: An Enterprise Architect’s View of MongoDBMongoDB
In the world of big data, legacy modernization, siloed organizations, empowered customers, and mobile devices, making informed choices about your enterprise infrastructure has become more important than ever. The alternatives are abundant, and the successful Enterprise Architect must constantly discern which new technology is just a shiny object and which will add true business value.
MongoDB is more than just a great application database for developers; it gives Enterprise Architects new capabilities to solve previously difficult architectural requirements much more easily. Take for example the challenge of many siloed systems at MetLife – with MongoDB, the Metlife team was able to successfully provide a single view into those 70 systems, in only 3 months.
In this webinar, we will:
Explore real life challenges enterprises face with case studies of their solutions
Consider how best to introduce MongoDB in the enterprise
Give an overview of how to optimize the use of MongoDB
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.
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.
Join CIGNEX Datamatics, Alfresco’s Global Platinum Partner, as they share the case study experience of a leading global online university. Together we’ll take a close look at their document management and web portal solution and their integrations with Alfresco ECM, Liferay Portal and Moodle Learning Management System.
MongoDB and Our Journey from Old, Slow and Monolithic to Fast and Agile Micro...MongoDB
Jeremiah Ivan, VP of Engineering, Merrill Corporation
In the span of 12 months Merrill was able to move from a monolithic and hard-to-change architecture to a fast-moving, agile development platform, enabled by the MongoDB database. We’ll talk about the technology, people, and process changes involved in the transformation. We hope that participants in this session will come away with the bits and pieces of a recipe for success that they can apply to their environment.
MongoDb is a document oriented database and very flexible one as it gives horizontal scalability.
In this presentation basic study about mongodb with installation steps and basic commands are described.
MongoDB Evenings DC: Get MEAN and Lean with Docker and KubernetesMongoDB
Get MEAN and Lean with Docker and Kubernetes
Vadim Polyakov, Director of Enterprise Application Architecture, Inovalon
MongoDB Evenings DC
April 12, 2016 at 1776
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.
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.
Relational databases are being pushed beyond their limits because of the way we build and run applications today, coupled with growth in data sources and user loads. To address these challenges, many companies, such as MTV and Cisco have migrated successfully from relational databases to MongoDB.
This ingite length deck talks about why we have seen so much database innovation and the genesis of the NoSQL movement over the last 5 year. While there are many great NoSQL products it speaks to why MongoDB is dominating the space and is the heir apparent to the RDBMS for modern operational data.
How Enterprises are Using NoSQL for Mission-Critical ApplicationsDATAVERSITY
NoSQL databases including Couchbase are increasingly being selected as the backend technology for web and mobile apps. Document databases in particular are well suited for a large number of different use cases as an operational datastore.
In this webinar, Perry Krug, Principal Solutions Architect at Couchbase, will give a brief overview of Couchbase Server, a document database and its underlying distributed architecture. In addition, Perry will share how some of the biggest brands in the world use Couchbase, including:
Paypal A scalable NoSQL and big data architecture with real time analytics
Concur A highly available cache solution that supports 1B operations/day
Amadeus A backend data store that supports 1.6B transactions/day
MongoDB: The Operational Big Data by NORBERTO LEITE at Big Data Spain 2014Big Data Spain
When one starts analysing the BigData technology spectrum we can find several different solutions for several different purposes. This is may cause confusion, uncertainty and doubts on what to chose and what for. Both on technical and business decision makers. This talk is to shed some light on where you should consider MongoDB for your BigData strategy and how to make the most out of the dominant technologies of the field.
MongoDB is the leading NoSQL database due to a plenitude of reasons, open source, general purpose, document oriented database supported by a large community and educational platform. It's horizontal scalability features allows this to fit in the operational big data scenarios where the business needs point to realtime analytics and ever-increasing data sets. This talk will focus on the usage of MongoDB for big data operational purposes and why it's ideal to be used in such scenarios. Also integration with other notable big data technology out there like Hadoop and BI tools.
Norberto Leite - Senior Solutions Architect, @MongoDB.
Mongo DB presentation during the Pentaho & Big Data Ecosystem - Live Seminar 2013
MongoDB: How We Did It – Reanimating Identity at AOLMongoDB
AOL experienced explosive growth and needed a new database that was both flexible and easy to deploy with little effort. They chose MongoDB. Due to the complexity of internal systems and the data, most of the migration process was spent building a new identity platform and adapters for legacy apps to talk to MongoDB. Systems were migrated in 4 phases to ensure that users were not impacted during the switch. Turning on dual reads/writes to both legacy databases and MongoDB also helped get production traffic into MongoDB during the process. Ultimately, the project was successful with the help of MongoDB support. Today, the team has 15 shards, with 60-70 GB per shard.
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: Scaling MongoDB through Sharding - A Case Study with CIGNEX DatamaticsMongoDB
This webinar will walk through the solution CIGNEX developed for a real-time event logging application along with some of the key technical considerations, like selecting the proper shard key. Yash will explain the key decision factors and performance statistics that went into their solution. By selecting the correct shard key MongoDB is able to handle approximately 30 Million inserts and 5 million updates per hour. This case study will cover everything from hardware recommendations to cluster configuration management with scale.
MongoDB and Our Journey from Old, Slow and Monolithic to Fast and Agile Micro...MongoDB
Jeremiah Ivan, VP of Engineering, Merrill Corporation
In the span of 12 months Merrill was able to move from a monolithic and hard-to-change architecture to a fast-moving, agile development platform, enabled by the MongoDB database. We’ll talk about the technology, people, and process changes involved in the transformation. We hope that participants in this session will come away with the bits and pieces of a recipe for success that they can apply to their environment.
MongoDb is a document oriented database and very flexible one as it gives horizontal scalability.
In this presentation basic study about mongodb with installation steps and basic commands are described.
MongoDB Evenings DC: Get MEAN and Lean with Docker and KubernetesMongoDB
Get MEAN and Lean with Docker and Kubernetes
Vadim Polyakov, Director of Enterprise Application Architecture, Inovalon
MongoDB Evenings DC
April 12, 2016 at 1776
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.
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.
Relational databases are being pushed beyond their limits because of the way we build and run applications today, coupled with growth in data sources and user loads. To address these challenges, many companies, such as MTV and Cisco have migrated successfully from relational databases to MongoDB.
This ingite length deck talks about why we have seen so much database innovation and the genesis of the NoSQL movement over the last 5 year. While there are many great NoSQL products it speaks to why MongoDB is dominating the space and is the heir apparent to the RDBMS for modern operational data.
How Enterprises are Using NoSQL for Mission-Critical ApplicationsDATAVERSITY
NoSQL databases including Couchbase are increasingly being selected as the backend technology for web and mobile apps. Document databases in particular are well suited for a large number of different use cases as an operational datastore.
In this webinar, Perry Krug, Principal Solutions Architect at Couchbase, will give a brief overview of Couchbase Server, a document database and its underlying distributed architecture. In addition, Perry will share how some of the biggest brands in the world use Couchbase, including:
Paypal A scalable NoSQL and big data architecture with real time analytics
Concur A highly available cache solution that supports 1B operations/day
Amadeus A backend data store that supports 1.6B transactions/day
MongoDB: The Operational Big Data by NORBERTO LEITE at Big Data Spain 2014Big Data Spain
When one starts analysing the BigData technology spectrum we can find several different solutions for several different purposes. This is may cause confusion, uncertainty and doubts on what to chose and what for. Both on technical and business decision makers. This talk is to shed some light on where you should consider MongoDB for your BigData strategy and how to make the most out of the dominant technologies of the field.
MongoDB is the leading NoSQL database due to a plenitude of reasons, open source, general purpose, document oriented database supported by a large community and educational platform. It's horizontal scalability features allows this to fit in the operational big data scenarios where the business needs point to realtime analytics and ever-increasing data sets. This talk will focus on the usage of MongoDB for big data operational purposes and why it's ideal to be used in such scenarios. Also integration with other notable big data technology out there like Hadoop and BI tools.
Norberto Leite - Senior Solutions Architect, @MongoDB.
Mongo DB presentation during the Pentaho & Big Data Ecosystem - Live Seminar 2013
MongoDB: How We Did It – Reanimating Identity at AOLMongoDB
AOL experienced explosive growth and needed a new database that was both flexible and easy to deploy with little effort. They chose MongoDB. Due to the complexity of internal systems and the data, most of the migration process was spent building a new identity platform and adapters for legacy apps to talk to MongoDB. Systems were migrated in 4 phases to ensure that users were not impacted during the switch. Turning on dual reads/writes to both legacy databases and MongoDB also helped get production traffic into MongoDB during the process. Ultimately, the project was successful with the help of MongoDB support. Today, the team has 15 shards, with 60-70 GB per shard.
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: Scaling MongoDB through Sharding - A Case Study with CIGNEX DatamaticsMongoDB
This webinar will walk through the solution CIGNEX developed for a real-time event logging application along with some of the key technical considerations, like selecting the proper shard key. Yash will explain the key decision factors and performance statistics that went into their solution. By selecting the correct shard key MongoDB is able to handle approximately 30 Million inserts and 5 million updates per hour. This case study will cover everything from hardware recommendations to cluster configuration management with scale.
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
Webinar: Making A Single View of the Customer Real with MongoDBMongoDB
Tier 1 banks, top insurance providers and other global financial services institutions have discovered that with the use of MongoDB, they are able to achieve a single view of the customer. This allows them not only to comply with KYC and other regulations, but also to engage customers efficiently, which helps reduce churn and increase wallet share while 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).
Hortonworks Technical Workshop: HBase and Apache Phoenix Hortonworks
HBASE is the leading NoSQL database. Tightly integrated with Hadoop ecosystem, it offers random, real-time read/write capabilities on billions of rows and millions of columns. Apache Phoenix offers a SQL interface to HBASE, opening HBase to large community of SQL developers and enabling inter-operability with SQL compliant applications. The session will cover the essentials of HBASE and provide an in-depth insight into Apache Phoenix. Audience: Developers, Architects and System Engineers from the Hortonworks Technology Partner community. Recording:
https://hortonworks.webex.com/hortonworks/lsr.php?RCID=de6d0c435c0761adedf3114a100e7483%20
Speakers: Lars George and Jon Hsieh (Cloudera)
Today, there are hundreds of production HBase clusters running a multitude of applications and use cases. Many well-known implementations exercise opposite ends of the HBase's capabilities emphasizing either entity-centric schemas or event-based schemas. This talk presents these archetypes and others based on a use-case survey of clusters conducted by Cloudera's development, product, and services teams. By analyzing the data from the nearly 20,000 HBase cluster nodes Cloudera has under management, we'll categorize HBase users and their use cases into a few simple archetypes, describe workload patterns, and quantify the usage of advanced features. We'll also explain what an HBase user can do to alleviate pressure points from these fundamentally different workloads, and use these results will provide insight into what lies in HBase's future.
Apache Phoenix and Apache HBase: An Enterprise Grade Data WarehouseJosh Elser
An overview of Apache Phoenix and Apache HBase from the angle of a traditional data warehousing solution. This talk focuses on where this open-source architect fits into the market outlines the features and integrations of the product, showing that it is a viable alternative to traditional data warehousing solutions.
What started as a way for web giants to solve problems of serious scale has become the default way all enterprises manage Big Data. Despite having a catchy, if inaccurate title, there really isn't a coherent "NoSQL" category, nor is there a simple future for the range of NoSQL databases. In this presentation, Matt Asay will outline the reasons for NoSQL's existence and persistence, how the different NoSQL technologies help enterprises get control of Big Data, and will identify the trends that point to a bright future for post-relational databases.
Introduzione generale di che cos'è MongoDB e quali sono i benefici che può introdurre in ambito aziendale per migliorare processi aziendali e performances.
MongoDB è uno degli elementi tecnologici necessari per costruire le basi dell'internet delle cose e Big Data in ambito aziendale.
Adoption of MongoDB has accelerated tremendously among developers in the past 18 months, and many large enterprises have now deployed MongoDB in reliable and large scale production environments. However, for many developers, it remains a challenge to convince production teams and business stakeholders to adopt an open source technology that has not been certified yet by their IT teams. This session will provide you with the compelling arguments to reassure business and production teams such as:
Public customer references and real-world case studies (migration, and adoption stories)
Deployment support and practices for robustness
How MongoDB contributes to your company’s business value
Webinar: How Partners Can Benefit from our New Program (EMEA)MongoDB
The 10gen partner ecosystem is growing quickly and includes leading software, hardware, cloud, channel and services companies who develop, market, sell and support solutions based on the MongoDB document database. We've created a Partner Program designed for companies looking to efficiently build new business or revenue streams based on MongoDB and capitalize on big data, cloud, mobile and other computing trends and opportunities related to our document-oriented database.
Join this webinar for an introduction to 10gen, MongoDB and our partnership program. We're going to explain the benefits of becoming a a partner and common use cases and verticals for MongoDB. Directions and contacts will be given to companies interested in partnering with us in EMEA.
Webinar: Expanding Retail Frontiers with MongoDBMongoDB
Twenty-first century retailers are facing an increasingly challenging and competitive environment. Given the rise of ecommerce and pressure on margins, retailers are looking for innovative services as well as ways to improve customer service, loyalty and engagement. Leading organizations in retail are choosing MongoDB because of its ability to help them compete, providing superior customer experience and accelerated time to market. In this webinar, hear how MongoDB enables retailers to develop:
Enriched Product Catalog Management
Distribution and Logistics Management
Solutions Real time Analysis of Customer Behavior
The use cases are specific to retail, but the patterns of usage - agility, scale, and global distribution - will be applicable across many industries.
Since inception of MongoDB as a NoSQL database system, roughly half of deployments have been on commercial cloud, providing Infrastructure as a Service. Business users have realized benefit of instant, elastic procurement of servers and offloading costs from traditional data center architecture. The next phase of cloud service architecture is Database as a Service, which has been accelerating dramatically the last year among large enterprise customers of MongoDB. We will explore integration with varying enterprise cloud architectural requirements, MongoDB best practices as applied to fundamental architectural choices, and collaboration with the business owners to ensure a good match of needs and value. We will also address accounting, chargeback integration, and quanification of benefits to the enterprise, such as standardizing elastic architecture and offloading database system maintenance costs.
Webinar: How Banks Manage Reference Data with MongoDBMongoDB
Managing and distributing reference data globally has always been a challenge for financial institutions. Managing and maintaining database schemas while integrating and replicating that data across geographies is costly and time consuming. MongoDB's native replication capabilities and partitioned architecture make it simple to distribute and synchronize data efficiently across the globe. MongoDB’s dynamic schema dramatically reduces database maintenance for schema migrations – data structure changes can be applied with no down time, and with no impact to existing applications.
Why Organizations are Looking at Alternative Database Technologies – Introduc...DATAVERSITY
This webinar will first walk through the main forces driving developers and IT organizations to adopt non-relational or NoSQL databases. Next it will cover the key concepts and terminology used in the NoSQL space. Finally, using MongoDB as an example, the webinar will highlight examples of how organizations have put NoSQL technology to use in order to drive their business objectives.
Similar to An Evening with MongoDB Detroit 2013 (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
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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
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MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB
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MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB
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MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB
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MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB
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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.
3. Introduction
10gen is the company behind MongoDB –
the leading NoSQL database
Document- General Open-
Oriented Purpose Source
3
4. 10gen Overview
170+ employees 500+ customers
Offices in New York, Palo Alto, Washington
Over $81 million in funding DC, London, Dublin, Barcelona and Sydney
4
6. Global MongoDB Community
41,000+
Monthly Unique Downloads
24,000+
Online Education Registrants
12,000+
MongoDB User Group Members
10,000+
Annual MongoDB Days Attendees
6
8. Relational Database Challenges
Data Types Agile Development
• Unstructured data • Iterative
• Semi-structured • Short development
data cycles
• Polymorphic data • New workloads
Volume of Data New Architectures
• Petabytes of data • Horizontal scaling
• Trillions of records • Commodity
servers
• Millions of queries per
second • Cloud computing
8
16. MongoDB Features
JSON Data Model with Auto-Sharding for
Dynamic Schema Horizontal Scalability
Flexible, Full Index Rich, Document-Based
Support Queries
Built-In Replication and Fast, In-Place
High Availability Updates
Aggregation Framework and GridFS for Large File
Map/Reduce Storage
16
17. MongoDB Monitoring Service (MMS)
Free, cloud-based service for monitoring and alerts
• Charts, custom
dashboards and
automated alerting
• Tracks 100+ metrics –
performance, resource
utilization, availability
and response times
• 10,000+ users
17
18. Best Total Cost of Ownership (TCO)
Developer and Ops Savings
• Less code
• More productive development
• Easier to maintain
Hardware Savings
• Commodity servers
• Internal storage (no SAN)
• Scale out, not up
Software and Support Savings
• No upfront license – pay for value DB Alternative
over time
• Cost visibility for usage growth
18
19. 10gen Products and Services
Subscriptions
Professional Support, Subscriber Edition and Commercial License
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Expert Resources for All Phases of MongoDB Implementations
Training
Online and In-Person for Developers and Administrators
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23. Case Study
Stores user and location-based data in MongoDB
for social networking mobile app
Problem Why MongoDB Results
• Relational architecture • Auto-sharding to scale • Focus engineering on
could not scale high-traffic and fast- building mobile app vs.
growing application back-end
• Check-in data growth
hit single-node capacity • Geo-indexing for easy • Scale efficiently with
ceiling querying of location- limited resources
based data
• Significant work to build • Increased developer
custom sharding layer • Simple data model productivity
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24. Case Study
Relies on a MongoDB-powered, real-time analytics
product for SMBs
Problem Why MongoDB Results
• More than 500,000 • Ability to handle • Shorter feature
websites complex data while development cycles
maintaining high (e.g., 1 week)
• 10 years of complex performance
data • 2.5x faster than MySQL
• Took 1 week for devs to
• Relational database ramp up on MongoDB • High-performance real-
took several days to time analytics to over
process data • Strong community 500,000 SMBs
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25. Case Study
Stores billions of posts in myriad formats with
MongoDB
Problem Why MongoDB Results
• 1.5M posts per day, • Flexible document- • Initial deployment held
different structures based model over 5B documents and
• Inflexible MySQL, 10TB of data
• Horizontal scalability
lengthy delays for built in • Automated failover
making changes
provides high
• Data piling up in • Easy to use availability
production database • Interface in familiar • Schema changes are
• Poor performance language quick and easy
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26. Get Involved
Speak at a MongoDB
meetups@10gen.com
User Group
Get MongoDB News
10gen.com/signup
and Updates
26
27. For More Information
Resource Location
MongoDB Downloads www.mongodb.org/download
Free Online Training education.10gen.com
Webinars and Events www.10gen.com/events
White Papers www.10gen.com/white-papers
Case Studies www.10gen.com/customers
Presentations www.10gen.com/presentations
Documentation docs.mongodb.org
Additional Info info@10gen.com
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28.
29. Case Study
Serves targeted content to users using MongoDB-
powered identity system
Problem Why MongoDB Results
• 20M+ unique visitors • Easy-to-manage • Rapid rollout of new
per month dynamic data model features
enables limitless
• Rigid relational schema growth, interactive • Customized, social
unable to evolve with content conversations
changing data types throughout site
and new features • Support for ad hoc
queries • Tracks user data to
• Slow development increase
cycles • Highly extensible engagement, revenue
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30. Case Study
Uses MongoDB to safeguard over 6 billion images
served to millions of customers
Problem Why MongoDB Results
• 6B images, 20TB of • JSON-based data • 5x cost reduction
data model
• 9x performance
• Brittle code base on top • Agile, high improvement
of Oracle database – performance, scalable
hard to scale, add • Faster time-to-market
features • Alignment with
Shutterfly’s services- • Dev cycles in weeks vs.
• High SW and HW costs based architecture tens of months
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31. Case Study
Stores one of world’s largest record repositories
and searchable catalogues in MongoDB
Problem Why MongoDB Results
• One of world’s largest • Fast, easy scalability • Will scale to 100s of TB
record repositories by 2013, PB by 2020
• Full query language
• Move to SOA required • Searchable catalogue
new approach to data • Complex metadata of varied data types
store storage
• Decreased SW and
• RDBMS could not support costs
support centralized data
mgt and federation of
information services
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32. Case Study
Provides low-latency, high-scale translation
management platform built on MongoDB
Problem Why MongoDB Results
• Old MySQL • Horizontal scale with built- • Simplified scaling and
performance in sharding high-performance
degradation and high architecture
maintenance • High availability with
replica sets • Dramatically improved
• Complex to scale
MySQL developer productivity
• Memory-mapped
• High- architecture for ingesting • Increased uptime
speed, asynchronous content quickly w/out
storage and fast read separate caching layer
requirements
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33. Case Study
Uses MongoDB to power real-time ad serving
platform
Problem Why MongoDB Results
• Needed costly SQL • Dynamic schema enables • Billions of requests per
architecture to enable continuous algorithm day with sub-ms latency
real-time bidding development and
customer-specific fields • Inexpensive cost per
• Large volumes of data query
and queries • Scalability for massive
data volumes and low • TB of data stored,
• Diverse, evolving latency populated on the fly and
schema queried in real-time
• Visual monitoring with
MMS
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34. Case Study
Uses MongoDB to underpin social media monitoring
and recommendation engine
Problem Why MongoDB Results
• HBase locked them into • Ease of use and flexibility • Robust queries and
rigid data model, stifling of data model dynamic schema
ability to create enable higher quality
connections between • Powerful indexing and ad recommendations
data sets hoc querying, plus
integrated MapReduce • Bugs fixed in hours
• Single points of failure instead of days
with master/slave • High availability with
topology replica sets • Dramatically improved
uptime
• Up to 1M posts per day
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35. Case Study
Stores 3.5 TB of data in MongoDB to power
real-time dictionary
Problem Why MongoDB Results
• Performance • Easy to • Migrated 5B records in
roadblocks with MySQL store, locate, retrieve data 1 day, zero downtime
• Massive data ingestion • Eliminated Memcached • Reduced code by 75%
led to database outages while increasing
performance: up to 2M • Sped up document
• Tables locked for tens requests per hour, 8,000 metadata retrieval from
of seconds during words inserted per 30 ms to 0.1 ms
inserts second • Significant cost
• Long runway for scale-out savings, 15% reduction
in servers
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36. Case Study
Self-service product built on MongoDB enables
real-time analytics for social marketing
Problem Why MongoDB Results
• Need for real-time • Real-time aggregation to • Operational cost
aggregation and adjust campaigns on the savings
analytics fly
• Simplified scale-out to
• Tried SQL, then • Scalability for persistence support 140M
MapReduce – both layer impressions
solutions only handled
periodic data, could not • Ability to store large • Data flexibility to add
scale amounts of data reliably new features and
performance gains
without overhead
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37. Case Study
Runs unified data store serving hundreds of
diverse web properties on MongoDB
Problem Why MongoDB Results
• Hundreds of diverse • Flexible schema • Developers can focus on
web properties built on end-user features instead
Java-based CMS • Rich querying and support of back-end storage
for secondary index
• Rich documents forced support • Simplified day-to-day
into ill-suited model operations
• Easy to manage
• Adding new data types, replication and scaling • Simple to add new brands,
tables to RDBMS killed content types, etc. to
read performance platform
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38. Case Study
MongoDB serves as social gaming platform for
hundreds of millions of users
Problem Why MongoDB Results
• Legacy MySQL • Flexible data model • Improved game
hindered development applicable to wide variety performance and end-user
speed, could not scale of use cases experience
• Needed operational • High availability through • Server cost reduction
database that could replica sets on commodity
also handle real-time servers • Accelerated development
analysis and time-to-market
• Size and strength of
• Server sprawl MongoDB community
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39. Case Study
Delivers agile automated supply chain service to
retailers powered by MongoDB
Problem Why MongoDB Results
• RDBMS poorly- • Document-oriented model • Decreased supplier
equipped to handle less complex, easier to onboard time by 12x
varying data types code
(e.g., SKUs, images) • Grew from 400K records to
• Single data store for 40M in 12 months
• Inefficient use of structured, semi-
storage in RDBMS structured and • Significant cost reductions
(i.e., 90% empty unstructured data on schema design time,
columns) ongoing developer effort,
• Scalability and availability and storage usage
• Complex joins
degraded performance • Analytics with
MapReduce
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40. Case Study
Runs social marketing suite with real-time
analytics on MongoDB
Problem Why MongoDB Results
• RDBMS could not meet • Ease of use, developer • Decreased app
speed and scale ramp-up development from months
requirements of to weeks
measuring massive • Solution maturity – depth
online activity of functionality, failover • 30M social events per day
• Inability to provide real- stored in MongoDB
• High-performance with
time analytics and write-heavy system • 6x increase in customers
aggregations
supported over one year
• Queuing and logging for
• Unpredictable peak
loads easy search at app layer
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41. Case Study
Real-time server and website monitoring
solution runs on MongoDB
Problem Why MongoDB Results
• Needed to handle • General purpose DB • MongoDB-first policy
thousands of requests
per second • High-write throughput • 12+ TB ingested per
month
• MySQL resulted in • Scales easily while
millions of rows per maintaining performance • Increased performance,
month, per server decreased disk usage
• Easy-to-use replication
• Difficult to scale MySQL and automated failover • Simplified infrastructure
with replication cuts costs, frees up
• Native PHP and Python resources for dev
drivers
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42. Case Study
Social e-commerce application built on MongoDB
offers 100M+ products from over 30K brands
Problem Why MongoDB Results
• MySQL could not • Flexible data model to • Boosted developer
accommodate growth handle varying product productivity
attributes
• Significant optimization • Scaled from 5M to
required to tune MySQL • Scalability for global reach 100M products with
performance minimal work
• Ease of maintenance
• Database maintenance • Decreased product
inhibited development • Consistent performance import time by 90%
even when adding data
and new features
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