Big Data and Wee Data by Avery Rosen

Big Data and Wee Data - We all know MongoDB is great for Big Data, but it's also great for work on the other end of the scale -- call it "Wee Data". In this talk, MongoDB expert and Principal at Bringing Fire Consulting, Avery Rosen, talks on how this type of data is far more common than Big Data scenarios. Avery discusses how just about every project starts with it. In this domain, we don't care about disk access and indices; instead, we care about skipping past the wheel inventing and getting right down to playing with the data. MongoDB lets you persist your prototype or small-working-set data without making you deal with freeze-drying and reconstitution, provides structure well beyond csv, gets out of your way as you evolve your schemas, and provides simple tools for introspecting data and crunching numbers. This talk was recorded at the New York MongoDB User Group meetup at


Correction note: At minute 24:30 - Shutterfly's (not photobucket's) migration to MongDb

Correction note: At minute 49:50 (regarding CouchDB) - CouchDB offers some very similar facilities to MongoDB, being a JSON-document storing database, and it does offer aggregation. However, it seems to have more config overhead in the form of views, and requires error-prone and difficult to diagnose javascript based map reduce instead of aggregation operations, and as such I maintain MongoDB is a superior choice for wee data projects.

"MongoDB and Wee Data: Hacking a Workflow" will start with theory and proceed to walk through ruby code that shows MongoDB's place in a working ecommerce site's data ecosystem.

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