There’s a lot of buzz on the NoSQL, or anti-RDBMS, meme lately.  But, I don’t like those category names. NoSQL? It’s a backwards ref, instead of a forwards-looking connotation.

Folks used to use the words “horseless carriage” when refering to those fancy new contraptions that you rode around in without using a horse.  Before long, though, new terms like automobile and “car” popped up.  Fast forward to today, and it’s now safe to call these things Mustangs, Broncos or Pintos without confusing anyone. I would already like to get a new category name for all these new kinds of datastores. I’ve heard of “AltDB”, but it’s still a backwards ref.  Alternative to RDBMS?  But, the truth is, you’ll probably never get rid of your RDBMS.  These new things are complements to RDBMS databases. The common refrain to me is this: you can scale out these systems by just adding more nodes or servers. How about a category label that connotates that benefit: JustAddMoreNodesDB — Jam-N-DB.  Jam-N-Database. By the way, there’s one more reason why I dislike the NoSQL/anti-RDBMS labeling… In the long term, my bet is these just-add-more-node systems will pick up more and more little bits of relational and SQL-like functionality.  For example, that’s already happening in Hadoop-land, which plays in the batch processing, analytics world.  In Hadoop, you write map-reduce programs instead of SQL queries.  But, additional pieces like Hive let us write SQL-like queries, which get automatically converted into map-reduce programs underneath the hood (a car analogy!).  Long live SQL.

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Posted by The Couchbase Team

Jennifer Garcia is a Senior Web Manager at Couchbase Inc. As the website manager, Jennifer has overall responsibility for the website properties including design, implementation, content, and performance.

One Comment

  1. Doesn\’t this miss the point? NoSQL is a poor label because SQL is too useful to discard.
    However, we are seeing a paradigm shift from RDMS to non-RDMS.
    Big Data (the 5Vs) is here to stay but RDMS are unable store or query it!
    Hence, many different data models will needed in addition to the relational model which has dominated the field for the past 30 odd years.

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