Learn how Elasticsearch and OpenSearch differ in their key features, development activity, technology stack and community adoption, so you can decide which of these search engines is best for you.

Elasticsearch appears to have several advantages over OpenSearch, particularly in popularity, maturity and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Elasticsearch significantly outpaces OpenSearch in community adoption with 77,843 stars compared to 13,506 stars on GitHub. This 5.8x difference suggests Elasticsearch has a much larger and more active community. In terms of developer contributions, Elasticsearch has 26,056 forks, indicating strong developer engagement.
Elasticsearch and OpenSearch are moving at much the same rate, adding 224 stars and adding 35 stars respectively over the last 30 days (+0.3% vs +0.3%). Neither is pulling away from the other on momentum alone.
Both projects show recent activity, with Elasticsearch last updated 46 minutes ago and OpenSearch 14 hours ago.
Both tools share common technology foundations, being built with Bash, Python, Java. However, they differ in their additional technology choices: Elasticsearch uses JavaScript, CSS, Typescript, C, Objective-C, C++.
Elasticsearch has been in development longer, starting 17 years ago, compared to OpenSearch which began 6 years ago. This 11.1-year head start suggests Elasticsearch may have more mature features and established processes.
OpenSearch is licensed under Apache-2.0, while Elasticsearch's license terms are not publicly specified.
Both tools serve similar use cases in Search Engines. However, they also have distinct specializations: Elasticsearch also focuses on Log Management, NoSQL & Document Databases.
Elasticsearch provides self-hosting options for complete data control and customization, while OpenSearch may be primarily cloud-based or require different deployment approaches.

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