Why Elastic Search is gaining more popularity than Solr?

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Solr and Elastic Search both are built on top of Lucene library. Both are compratively equal. It is comparing apples to apples. I have used both and I love both.

Lucene and Solr are part of Apache and they maintain same release cycle and version number for both. Any new feature / enhancement which get introduced in Lucene, will also get added to Solr. But still Elastic Search which uses Lucene as it core gained more popularity than Solr in recent years. Check out database ranking from DB-engines.

DB Ranking

What could be the reason?

Cloud Support:

Elastic Search is first to come up with cloud support. Solr added "Solr cloud" support later and they have dependency of ZooKeeper.

ELK Stack:

Elastic Search introduced ELK stack, which is nothing but Elastic Search, Log stash, Kibbana. ELK Stack primarly helps to search and monitor logs. Log stash is used as Log collector, it collects logs from various sources. Elastic Search is used for search. Kibbana is a visualization tool, it retreives data from Elastic Search and displays them in a nice graph. Elastic Search acquired both Logstash and Kibbana to offer complete solution to its customer.

Most of the Enterprise and Cloud products generate huge amount of logs and seriously they don't know how to search and analyze the logs. Splunk is a great commericial tool which is used for this purpose. Most of the companies used Splunk but it is too expensive. ELK Stack came to resuce for those want to analyze the logs. ELK stack got introduced in to most of the organization and its gained more popularity especially in Enterprise and Cloud related product organizations.

Packaging and providing as Solution

Elastic Search introduced other products and packaged as a solution. It's making life easier.

  • Shield - Provide security and protect the data
  • Beats  - Ship data to Elastic Search
  • Marvel - Monitor your Elasticsearch deployment.
  • Watcher- Alerting for Elasticsearch.

Every product is great but timing the feature and releases will gain more users and faster reach. Elastic Search is an example for that.     

 


   

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