Search and data analytics systems play a key role in today’s IT environments – from infrastructure monitoring and business analytics to indexing vast collections of documents. Two popular solutions in this space are Elasticsearch and OpenSearch. While they share common roots, they now differ in terms of licensing, development, and deployment strategies. So, which one should you choose?

Origins and background

Elasticsearch, developed by Elastic, gained popularity as a fast, scalable search engine built on Apache Lucene. For years, it was developed as an open-source project, but eventually transitioned to a more restrictive Server Side Public License (SSPL), sparking controversy within the community.

In response to this shift, Amazon – one of the main users of Elasticsearch – decided to create OpenSearch as a fully open-source fork of the project. OpenSearch is based on Elasticsearch version 7.10 (the last version released under the Apache 2.0 license) and is now developed as an independent open-source project, supported by AWS and the community.

Licensing and openness

This is one of the most critical differences between the two projects.

• Elasticsearch: Since version 7.11, it has been licensed under SSPL, which is not recognized as an open-source license by the Open Source Initiative (OSI). This includes restrictions on commercial use as a service (SaaS) without additional fees or vendor approval.
• OpenSearch: Fully licensed under Apache 2.0 – it’s 100% open source. Users have complete freedom to deploy, modify, and distribute it without limitations.

If your organization values full technological transparency or requires a purely open-source solution, OpenSearch is the natural choice.

Features and development

At a fundamental level, both engines offer similar capabilities – full-text search, aggregations, REST API queries, JSON support, replication, and horizontal scaling.

However, their development paths have diverged:

• Elasticsearch offers modern features such as Elastic Security, Elastic APM, built-in dashboards (Kibana), and advanced ML/AI capabilities (e.g., anomaly detection) – though many of these are only available in paid versions (Elastic Stack – Basic, Gold, Platinum).
• OpenSearch has developed its own interface – OpenSearch Dashboards, replacing Kibana. The project is rapidly implementing monitoring, alerting, and log processing features, along with plugins for security and alert management – all available as open source.

From the perspective of an organization looking for a free but complete solution, OpenSearch has the edge because it doesn’t place essential features behind a paywall.

Source: OpenSearch

Compatibility and migration

If your environment currently runs Elasticsearch 7.x, migrating to OpenSearch 1.x or 2.x is technically feasible, though it requires testing and preparation (especially when using custom plugins or scripts).

Since the projects have diverged, migrating from newer versions of Elasticsearch (e.g., 8.x) to OpenSearch is no longer trivial. On the other hand, for new deployments, it’s worth planning carefully and choosing one path from the start, as switching between them may become increasingly difficult over time.

Ecosystem and support

Elasticsearch boasts a large ecosystem, official tools (Logstash, Beats, Kibana), and a broad user base. Elastic also offers professional technical support, training, and subscription packages.

OpenSearch is developing its own suite of tools, has an active community, and is strongly backed by AWS (which uses OpenSearch in its Amazon OpenSearch Service). Third-party support is also available, and both the documentation and roadmap are publicly accessible.

So, which one to choose?

The decision between Elasticsearch and OpenSearch depends on several factors:

Both Elasticsearch and OpenSearch are powerful tools for data processing and analysis. The key differences lie in their development philosophy and licensing models. OpenSearch stands out where flexibility, openness, and lack of licensing costs are essential. Elasticsearch still leads in terms of ecosystem and integrations but is moving increasingly toward commercialization.

Therefore, before choosing, it’s worth clearly defining your expectations: openness and independence – or ready-made support from a commercial provider.

Want to talk about Elasticsearch or OpenSearch (or both)? Get in touch with us!