One of the challenges that comes with moving to MongoDB is figuring how to best model your data. While most developers have internalized the rules of thumb for designing schemas for RDBMSs, these rules don’t always apply to MongoDB. The simple fact that documents can represent rich, schema-free data structures means that we have a lot of viable alternatives to the standard, normalized, relational model. Not only that, MongoDB has several unique features, such as atomic updates and indexed array keys, that greatly influence the kinds of schemas that make sense. Understandably, this begets good questions:
In this session, we’ll answer these questions and more, provide a number of data modeling rules of thumb, and discuss the tradeoffs of various data modeling strategies.
Antoine Girbal, 10gen
Antoine Girbal works on MongoDB core apps and the Java driver. He previously spent many years in the CDN industry, at Panther CDN then CDNetworks, designing and developing one of the largest and fastest Content Delivery and Application Acceleration Network. Before switching to 10gen, he worked on a system spawning thousands of servers in 120 locations around the globe, serving about 1 million rps, and 200 gbps. Prior work include the development of a new network protocol in Linux kernel to multiplex several interfaces, used in wireless devices. Antoine received a MS degree in Computer Science from Stevens Institute (Hoboken), and a BS in Computer Science from Epita (Paris France).