ElasticSearch is an amazing tool for indexing and full-text search. It uses a Domain Specific query Language (DSL) which is JSON based and simple enough to understand but at the same time, very powerful. This makes ElasticSearch a standard for search integration in a web app.
But how good is ElasticSearch when it comes to using it as an analytics backend? Is it really something that can replace Hadoop anytime soon?
An advanced analytics system like Hadoop or ElasticSearch is something you’ll need when the data you get has outgrown the capabilities of Google Analytics, Amplitude, MixPanel or the likes. These tools are great for simple analytics and metrics. But when it comes to questions which can only be answered by custom queries — or the amount of data being collected is huge. While a lot of the legacy systems for advanced analytics are built on top of Hadoop, more developers are starting to use ElasticSearch for it. Here we’ll analyze if ElasticSearch really is a good alternative for advanced analytics or does Hadoop still win.