MongoDB at Scale

Do Things Big

Tens of thousands of organizations use MongoDB to build high-performance systems at scale. Over 30 of the Fortune 100 and many of the most successful and innovative web companies rely on MongoDB. They’ve grown from single server deployments to clusters with over 1,000 nodes, delivering millions of operations per second on over 100 billion documents and petabytes of data.

Scalability is not just about speed. It’s about 3 different metrics, which often work together:

  • Cluster scale: Distributing the database across 100+ nodes, often in multiple data centers
  • Performance scale: Sustaining 100,000+ database read and writes per second while maintaining strict latency SLAs
  • Data scale: Storing 1 billion+ documents in the database
  • There are many examples of MongoDB users who are pushing the limits to scalability. Here are a few, organized around each scaling dimension.

    Cluster Scale

    EA Sports FIFA is the world's best-selling sports video game franchise. To serve millions of players, EA’s Spearhead development studio selected MongoDB to store user data and game state. Auto-sharding makes it simple to scale MongoDB across EA’s 250+ servers with no limits to growth as EA FIFA wins more fans.

    The largest search engine in Russia uses MongoDB to manage all user and metadata for its file sharing service. MongoDB has scaledto support tens of billions of objects and TBs of data, growing at 10 million new file uploads per day.

    The world’s largest online auction site uses MongoDB to store all media metadata for the site. This includes references to images of every item for sale on eBay. The MongoDB cluster is deployed across multiple data centers and delivers 99.999% availability.

    Sporting Solutions is a ground-breaking sports betting software and data services company. Pairing its market leading skills in data science, modelling and sports trading with MongoDB enables Sporting Solutions to scale beyond the limits of relational technology for in-play betting. The Sporting Solutions database cluster comprises hundreds of MongoDB nodes deployed across an OpenStack public cloud and on-premise data centers, including full integration with Hadoop.

    Performance Scale

    Foursquare is used by over 50 million people worldwide, who have checked in over 6 billion times, with millions more added every day. MongoDB is Foursquare’s main database, supporting hundreds of thousands of operations per second and storing all check-ins and history, user and venue data along with reviews.

    AHL, a part of Man Group plc, is a quantitative investment manager based in London and Hong Kong, with over $11.3 billion in assets under management. After evaluating multiple technology options, AHL used MongoDB to replace its relational and specialised "tick" databases. MongoDB supports 250 million ticks per second, at 40x lower cost than the legacy technologies it replaced.

    MongoDB supports over 100 applications deployed on over 1,000 nodes, delivering 20 billion operations per day. Core Internet services including content management, chat, file sharing, and clickstream logging rely on MongoDB’s scalability and performance to serve hundreds of millions of users.

    One of the world’s top 5 banks powers its global reference data management platform with MongoDB. Replicating data across 12 data centers distributed around the world, MongoDB scales to serve the latest financial data to support traders in every country, while ensuring regulatory compliance.

    Data Scale

    MongoDB clusters routinely store hundreds of terabytes, and some store multiple petabytes of data. Over 150 clusters store more than 1 billion documents. Many store more than 100 billion documents. Deployments include:

    MongoDB powers McAfee Global Threat Intelligence (GTI), a cloud-based intelligence service that correlates data from millions of sensors around the globe. Billions of documents are stored and analyzed in MongoDB to deliver real-time threat intelligence to other McAfee end-client products.

    Many of the world’s most recognizable brands use Adobe Experience Manager to accelerate development of digital experiences that increase customer loyalty, engagement and demand. Adobe uses MongoDB to store petabytes of data the large-scale content repositories underpinning the Experience Manager.

    With 80 million classified ads posted every month, Craigslist needs to archive billions of records in multiple formats, and must be able to query and report on these archives at runtime. Craigslist migrated from MySQL to MongoDB to supports its active archive, with the continuous availability mandated for regulatory compliance across 700 sites in 70 different countries.

    CARFAX relies on its Vehicle History database to connect potential buyers with used vehicles in their area, and for analytics to guide the business. To improve customer experience, CARFAX migrated to MongoDB which now manages over 13 billion documents, before replication across multiple data centers.

    Other examples of extreme data scale on MongoDB:

  • Wordnik Content management for a live dictionary 6x larger than the Oxford English Dictionary.
  • RMS Data storage and analytics for global risk management on trillions of documents.

    The Easiest Way to Scale

    MongoDB Management Service (MMS) makes it easy to scale. You can provision and scale sharded clusters across multiple data centers in a single click.

    You can’t optimize what you can’t measure. With MMS, visualize over 100 performance metrics and tune your deployment. Set up custom alerts that trigger when metrics go out of range, so you can discover performance issues before your users do. Try MMS for free.

    Hassle-Free Scaling

    With MongoDB Consulting, solve scaling and high availability. A MongoDB consulting engineer provides expert guidance on the inner workings of sharding MongoDB, as well as replication, failover, and backup. The engineer then gives you detailed recommendations on how to apply best practices to your deployment.

    Learn More

    Download MongoDB Performance Best Practices

    Do You Scale?

    Send a note to us about your deployment to humongous@mongodb.com. We’d love to hear your story.