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What does Elastic do?

Elasticsearch is a popular open source database for storing and searching unstructured data.

databases

Last updated: July 4, 2025

The TL;DR

Elastic is the commercial company behind Elasticsearch, a popular open source database for storing and searching unstructured data.

  • Companies collect loads of unstructured data in the form of logs, requests, sessions, server metrics, etc.
  • Elasticsearch is a database to store that data, and a search engine to easily comb through it
  • Unlike MongoDB or MySQL, Elasticsearch is an analytical database, not a production one
  • Elasticsearch is commonly used with Kibana, its sister data visualization tool

Elasticsearch is a highly popular option for use cases around log management, typically for larger companies. The company behind the open source software went public back in 2018 and has seen impressive growth, reaching $1.27 billion in revenue for 2024 — more than tripling their $400M figure from 2020 [1] From Elastic's most recent 10-K filing: Our total revenue was $1.267 billion, $1.069 billion, and $862.4 million for the years ended April 30, 2024, 2023 and 2022, respectively, representing year-over-year growth of 19% for the year ended April 30, 2024 and 24% for the year ended April 30, 2023..

Terms Mentioned

Companies Mentioned

Elastic logo

Elastic

$ESTC
AWS logo

AWS

$AMZN
MongoDB logo

MongoDB

$MDB
Snowflake logo

Snowflake

$SNOW
Hashicorp logo

Hashicorp

$HCP

The core Elastic product: search

When you think of search, you probably think about Google. But on the engineering side, developers need to search through a lot of stuff, especially logs of what’s happening on their servers and apps. Elasticsearch, and the managed service for it that Elastic (the company) provides, is a database and search engine for doing just that.

Elasticsearch’s primary use cases revolve around things that commonly need, well, search. One big theme centers around infrastructure management, but teams also use it for security and even user facing search engines. It’s also most commonly used with what’s called the ELK stack, which is a series of adjacent tools that help you use Elasticsearch like Kibana and Logstash.

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Another database? Some taxonomy

Yet another database!? Yes, my dear readers, another database. But Elasticsearch isn’t like other databases; it’s use case specific, meaning it was designed for doing specific things with particular types of data. One of its flagship features is also built-in search (hence the name), which is now becoming common in the NoSQL database world, but was novel when it first released. To understand any database, you first need to understand why teams use it, and it’s there we begin this installment of Technically.

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