What’s the perfect database management system (DBMS) architecture, where analytics is concerned? It seems as if everybody in business intelligence (BI), data warehousing (DW), and related areas has their own opinion on this topic. In fact, it’s more than just opinions. In the database wars, we have huge communities of vendors and users with substantial investments in one or more approaches—from traditional relational DBMSs to column-oriented, in-memory, dimensional, inverted indexing, and other approaches.

In the analytic database wars, new architectures are springing up everywhere, each with its own devotees and differentiators, and each with a go-to-market message that takes potshots at established approaches.  The “No SQL” movement is just the latest coalition to emerge in this titanic struggle, and is essentially a loose coalition of diverse approaches rallying around a common theme: that traditional RDBMSs and their SQL-based access languages are unfit, or at least, maladapted to the new world of cloud, social networking, and Web-oriented analytics applications.

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