Elasticsearch vs Logstash: What are the differences?
What is Elasticsearch? Open Source, Distributed, RESTful Search Engine. Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
What is Logstash? Collect, Parse, & Enrich Data. Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.
Elasticsearch can be classified as a tool in the "Search as a Service" category, while Logstash is grouped under "Log Management".
Some of the features offered by Elasticsearch are:
- Distributed and Highly Available Search Engine.
- Multi Tenant with Multi Types.
- Various set of APIs including RESTful
On the other hand, Logstash provides the following key features:
- Centralize data processing of all types
- Normalize varying schema and formats
- Quickly extend to custom log formats
"Powerful api" is the top reason why over 310 developers like Elasticsearch, while over 60 developers mention "Free" as the leading cause for choosing Logstash.
Elasticsearch and Logstash are both open source tools. Elasticsearch with 42.4K GitHub stars and 14.2K forks on GitHub appears to be more popular than Logstash with 10.3K GitHub stars and 2.78K GitHub forks.
According to the StackShare community, Elasticsearch has a broader approval, being mentioned in 2003 company stacks & 979 developers stacks; compared to Logstash, which is listed in 563 company stacks and 278 developer stacks.
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