The debate on the pros and cons of non-relational databases which are typically described as “NoSQL databases” has recently been heating up. The anti-NoSQL backlash is in full swing from the rebuttal to one of my recent posts of mine I saw mentioned in Dennis Forbes’s write-up The Impact of SSDs on Database Performance and the Performance Paradox of Data Explodification (aka Fighting the NoSQL mindset) and similar thoughts expressed in typical rant-y style by Ted Dziuba in his post I Can't Wait for NoSQL to Die.
This will probably be my last post on the topic for a while given that the discussion has now veered into religious debate territory similar to vi vs. emacs OR functional vs. object oriented programming. With that said…
It would be easy to write rebuttals of what Dziuba and Forbes have written but from what I can tell people are now talking past each other and are now defending entrenched positions. So instead I’ll leave this topic with an analogy. SQL databases are like automatic transmission and NoSQL databases are like manual transmission. Once you switch to NoSQL, you become responsible for a lot of work that the system takes care of automatically in a relational database system. Similar to what happens when you pick manual over automatic transmission. Secondly, NoSQL allows you to eke more performance out of the system by eliminating a lot of integrity checks done by relational databases from the database tier. Again, this is similar to how you can get more performance out of your car by driving a manual transmission versus an automatic transmission vehicle.
However the most notable similarity is that just like most of us can’t really take advantage of the benefits of a manual transmission vehicle because the majority of our driving is sitting in traffic on the way to and from work, there is a similar harsh reality in that most sites aren’t at Google or Facebook’s scale and thus have no need for a Bigtable or Cassandra. As I mentioned in my previous post, I believe a lot of problems people have with relational databases at web scale can be addressed by taking a hard look at adding in-memory caching solutions like memcached to their infrastructure before deciding the throw out their relational database systems.
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