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MongoDB Database as a Gateway Drug to NoSQL

posted May 25, 2012, 2:21 PM by Rick Hightower   [ updated Sep 30, 2012, 3:19 PM ]

MongoDB combinations of features, simplicity, community, and documentation make it successful. The product itself has high availability, journaling (which is not always a given with NoSQL solutions), replication, auto-sharding, map reduce, and an aggregation framework (so you don't have to use map-reduce directly for simple aggregations). MongoDB can scale reads as well as writes.

MongoDB is a good way to answer that question that has been nagging you, namely, What is NoSQL?

NoSQL, in general, has been reported to be more agile than full RDBMS/ SQL due to problems with schema migration of SQL based systems. Having been on large RDBMS systems and witnessing the trouble and toil of doing SQL schema migrations, I can tell you that this is a real pain to deal with. RDBMS / SQL often require a lot of upfront design or a lot schema migration later. In this way, NoSQL is viewed to be more agile in that it allows the applications worry about differences in versioning instead of forcing schema migration and larger upfront designs. To the MongoDB crowd, it is said that MongoDB has dynamic schema not no schema (sort of like the dynamic language versus untyped language argument from Ruby, Python, etc. developers).

MongoDB does not seem to require a lot of ramp up time. Their early success may be attributed to the quality and ease-of-use of their client drivers, which was more of an afterthought for other NoSQL solutions ("Hey here is our REST or XYZ wire protocol, deal with it yourself"). Compared to other NoSQL solution it has been said that MongoDB is easier to get started. Also with MongoDB many DevOps things come cheaply or free. This is not that there are never any problems or one should not do capacity planning. MongoDB has become for many an easy on ramp for NoSQL, a gateway drug if you will.

MongoDB was built to be fast. Speed is a good reason to pick MongoDB. Raw speed shaped architecture of MongoDB. Data is stored in memory using memory mapped files. This means that the virtual memory manager, a very highly optimized system function of modern operating systems, does the paging/caching. MongoDB also pads areas around documents so that they can be modified in place, making updates less expensive. MongoDB uses a binary protocol instead of REST like some other implementations. Also, data is stored in a binary format instead of text (JSON, XML), which could speed writes and reads.

Another reason MongoDB may do well is because it is easy to scale out reads and writes with replica sets and autosharding. You might expect if MongoDB is so great that there would be a lot of big names using them, and there are like: MTV, Craigslist, Disney, Shutterfly, Foursqaure,, The New York Times, Barclay’s, The Guardian, SAP, Forbes, National Archives UK, Intuit, github, LexisNexis and many more.

If you would like to learn more about MongoDB consider the following resources: