Elasticsearch (and ELK)
Elasticsearch is similar to Solr, as it exposes the capacities of Lucene on the web, in open source.
Elasticsearch is tailored for Big Data. Created by Shay Bannon, Elasticsearch is managed the Elastic company. Datafari uses the ELK stack for its analytics functionnalities.
From its inception, Elasticsearch wanted an easy-to-scale system, with a REST approach. Elasticsearch is also releasing special functionnalities dedicated to logs analysis, through Kibana and logstash.
IIt is a stable backbone, able to handle scalabality throughmachine clustering, easy to manage, and supporting REST calls.
You can get more technical information on the website of Elasticsearch. Contrarily to Solr, Elasticsearch is not a project from the Apache foundation, but uses the same licence. It is available under the Apache v2 licence. France Labs proposes its expertise to install, configure, extend and maintain Elasticsearch on your systems.
Elasticsearch is the open source search engine that became popular thanks to the big data needs. It proposes advanced functionnalities, it is highly configurable, and it can compete with proprietary solutions. A search engine, it is a technical building block, able to digest big data, and to make it available to users in a clever way, in a few milliseconds.
Historically, Elasticsearch is an evolution from the Apache Lucene project. The latter is the heart of the search engine, but is just a subset of the functionnalities achievable through Elasticsearch. Furthermore, Lucene is a java API, it needs to be integrated at the source code level, whereas Elasticsearch is standalone.
ElasticSearch is becoming the de facto search tool for web startups, and benefits from a wide users community.
Use cases for ElasticSearch
It is not obvious to imagine all the possible uses of Elasticsearch, that is why we expose here some of them.