ElasticSearch: Definition, Purpose, and Advantages2017-02-14T09:00:00.000Z 2017-02-14T09:00:00.000Z We received several requests from our customers regarding the ElasticSearch technology and similar tools. What is ElasticSearch and why we think it's a superior instrument over Solr and other? Check out our blog.
ElasticSearch is a search engine based on Lucene and developed using Java. There are other tools like Lucene itself, Solr, SolrCloud, and many others.
When you are developing a software project, you might face the question: what search engine to choose? There are two leaders in the industry: Solr and ElasticSearch (ES). Both projects are very mature and stable, have many useful features, both designed to perform similar tasks. Also, both ES and Solr are released under the Apache Software License.
So, how do you choose?
There is one main difference that makes these two engines stand apart: Solr is more geared towards the text search, while ElasticSearch handles analytical types of queries. For example, if you use metrics and monitoring, ES is the search engine for you.
Solr also gives you key metrics, but nowhere near as many as ElasticSearch. Also, ES has comprehensive monitoring and centralized logging tools like Sematext’s SPM Performance Monitoring and Logsene Log Management and Analytics are essential when you need to understand the incoming and outgoing operational data.
Here are a few reasons to choose ElasticSearch over Solr:
- ES is easier to scale when you have larger clusters with more data and more nodes
- ES is much simpler to start with, even when you do not yet understand how things work. (Granted, when the data increases and clusters grow, this might pose danger, but by then you’ll know your way around.)
- ES is much more dynamic than Solr and the data can easily move around the cluster.
Check out the 2019 statistics regarding the popularity of ElasticSearch vs Solr vs Lucene:
A few additional benefits for developers:
- If you work a lot with Node.js, API access is much easier in native JSON than it would be if you convert to XML and back.
- If you use CouchDB, ES is a convenient tool to use since its “river” mechanism plugs straight into the CouchDB’s replication stream.
- ES allows you to configure the schema over HTTP, which gives you more freedom
- ES’s configuration is minimalistic i.e. dynamic types and schemaless documents