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No SQL? No Problem! – No SQL Info Sources

March 19, 2016

One of my current technology explorations is polyglot persistence. I am now mainly through the reading stage and it is quite clear that No SQL databases can be quite useful in certain situations, as can relational databases. Using both No SQL and relational databases together in the same solution, each according to its strengths, is the essence of the polyglot persistence idea.

Here are some sources of information I’ve found to be most useful on No SQL databases, their strengths, weaknesses, and when and how they can be best used:

  • Martin Fowler’s book NoSQL Distilled (2013) has been immensely helpful in gaining an understanding of both the various DBs, their strengths and weaknesses, and key underlying issues like eventual consistency, sharding, replication, data models, versioning, etc. It is short little book that is truly distilled.  If you read only one thing, this should be it.
  • Also very useful is Data Access for Highly-Scalable Solutions (2013) from Microsoft Press and the Patterns and Practices group.  It is written with a cloud mindset, contains code examples, and goes into much more detail that Fowler’s book. Importantly, it shows examples of how to design for No SQL DBs. I found the first few pages of its Chapter 8 “Building a Polyglot Solution” to be an excellent summary of the strengths, weaknesses, and issues one must deal with in using a No SQL database. That chapter also presents an excellent succinct summary of general guidelines of when to use a Key-Value DB, a Document DB, a Column-Family DB, and a Graph DB on page 194 of the book.
  • The blog article I posted several months ago, CQRS Info Sources, contains links to good articles on techniques that themselves use No SQL persistence (sometimes by implication).  Reading these links aided me in seeing areas where NoSQL DBs could be useful.
  • Microsoft Press’s book Cloud Design Patterns contains a lot of useful information on patterns that can use NoSQL DBs; guidance on things like Data Partitioning, Data Replication; plus a primer on Data Consistency that promotes a good understanding of eventual consistency versus strong consistency (usually available with a relational DBs via transactions). Some of the patterns it describes that can be implemented with a NoSQL DB are Event Sourcing, CQRS, Sharding, and the Materialized View.

Finally, keep in mind that both books listed above advise that relational databases will typically be the best choice for the majority of database needs in a system, and to use No SQL DBs only when there are strong reasons to do so.  The costs of not using a relational DB, with its capability to automatically roll back transactions spanning multiple tables, can be quite substantial due to the complexity of programming the error compensation (rollbacks) by hand.

George Stevens

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