Data modeling is hard, especially in the world of distributed NoSQL stores. With relational databases, developers have tended to store normalized data and shape their query model around that structure. This can come back to bite you when it comes time to scale, as complex queries across dozens of tables begin to affect application performance. It’s common to find developers rethinking their data model as query latency increases under load. With NoSQL stores, developers must consider their query patterns from the outset of application development, designing their data model to fit those patterns. A number of techniques, new and old, can be used to allow for maximum performance and scalability. Topics covered will include: De-normalization, time boxing, conflict resolution, and convergent & commutative replicated data types. Additionally, discussions of common query patterns in light of the capabilities of various NoSQL data stores will be reviewed.

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