Why The Clock is Ticking for MongoDB

Last month, ZDNet published an interview with MongoDB CEO Max Schireson which took the position that the document databases, such as MongoDB, are better-suited to today's applications than traditional relational databases; the title of the article implies that the days of relational databases are numbered. But it is not, as Schireson would have us believe, that the relational database community is ignorant of or has not tried the design paradigms which he advocates, but that they have been tried and found, in many cases, to be anti-patterns. Certainly, there are some cases in which the schemaless design pattern that is perhaps MongoDB's most distinctive feature is just the right tool for the job, but it is also misleading to think that such designs must use a document store. Relational databases can also handle such workloads, and their capabilities in this area are improving rapidly.

Choosing a Datastore

In thinking about which database might be best for any particular job, it's easy to get lost in the PR. Advocates of traditional relational database systems like Oracle and PostgreSQL tend to focus on the fact that systems are feature-rich and provide features such as atomicity, consistency, isolation, and durability (ACID), while advocates of document databases (like MongoDB) and key-value stores (memcached, Dynamo, Riak, and many others) tend to focus on performance, horizontal scalability, and ease of configuration.  This is obviously an apples-and-oranges comparison, and a good deal of misunderstanding and finger-pointing can result.  Of course, the real situation is a bit more complicated: everyone really wants to have all of these features, and any trade-off between them is bound to be difficult.