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MongoDB Applied Design Patterns

Episode #109, published Sat, Apr 29, 2017, recorded Wed, Apr 26, 2017.

This episode is carbon neutral.
Database design and decisions use to be fairly straightforward. Pick your relational database engine, map out the general entities, apply the third-normal-form (3NF) to them and you're basically done.

With the Cambrian explosion of database options and variations created from 2009 to present, it gets much harder to even choose the database much less follow the well-worn path of 3NF.

On this episode, you'll meet Rick Copeland, a fellow MongoDB Master and author of the book MongoDB Applied Design Patterns. We will discuss modeling data using documents in a document database such as MongoDB and some techniques that particular apply to MongoDB's implementation.

Links from the show

Rick on twitter: @rick446
Rick's blog: blog.pythonisito.com

O'Reilly: MongoDB Applied Design Patterns: oreilly.com/product/0636920027041
Amazon: MongoDB Applied Design Patterns: amzn.to/2qx47oL
Rick's Mongo Course: packtpub.com

Ming ODM: ming.readthedocs.io
PyMongo: api.mongodb.com/python
MongoEngine: github.com/MongoEngine
MongoKit: github.com/namlook/mongokit
Mlab: mlab.com
MongoDB Atlas: mongodb.com/cloud/atlas

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Rick Copeland
Rick Copeland
Rick Copeland is the Principal Consultant of Arborian Consulting, which provides Python and MongoDB-focused consulting, training, and custom development services. Rick has been using Python since 2005, MongoDB since 2009, and has spoken at various user groups and conferences on both topics. He is a member of the Python Software Foundation and the Masters of MongoDB. Previously, Rick was a software engineer with SourceForge, where he helped reinvent and open-source the SourceForge platform as the Allura project.
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