Inside MongoDB SF 2014

Earlier this month, I attended MongoDB SF, the last stop of the MongoDB Days 2014 tour. Usually, I am reluctant to attend vendor-organized conferences because they tend to be more marketing opportunities than venues for gaining in depth understanding of the technology. However I was pleasantly surprised at the MongoDB event. Most of the presentations I heard were obviously delivered by the actual technology creators.

When using MongoDB I’ve found that its MapReduce facility is hard to use (and not just because of having to write your mapper and reducer in JavaScript) and does not really work well. In practice it is necessary to externalize the map/reduce jobs to Hadoop. So, I learned that the MongoDB team have confronted this problem and in response they developed an Hadoop connector. And of course they already offer an Elasticsearch connector because MongoDB is not great at facetted searches. All of these developments put MongoDB at the center of an eco-system. In this eco-system, tasks (that MongoDB is not good at) are passed to specialized third-party solutions. I need to think more about this (and to test it) but I am not 100% convinced by this architecture. I would prefer an architecture where all these tools (e.g., MongoDB, Hadoop, Eleasticsearch) are equal rather than depending on MongoDB.

Another interesting insight I got from attending the event is that the MongoDB team is looking at providing some type of schema validation. Although the way they want to achieve this is not clear yet, I think this is a step in the right direction. After all, data is used by applications that assume a certain data structure. In this context, having the database enforcing this data structure can only help because it allows you to write simpler code (by avoiding defensive programming) which speeds up processing (something important for big data) and cuts down on the possibility of coding errors. This is one of the objectives behind our facetted approach where a JSON schema is used to define the data structure of each facet and validate it before it is stored in the database.

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