OpenSearch vs. Elasticsearch

Elasticsearch was created by Elastic NV and originally distributed under the permissive Apache 2.0 license, which fueled its widespread adoption. However, in 2021, to prevent cloud providers from offering managed Elasticsearch services without contributing back, Elastic controversially switched its licensing to the non-open-source Server Side Public License (SSPL) and the Elastic License. This move restricted how the software could be used, particularly in commercial SaaS offerings.

In response, AWS, along with other partners, forked the last Apache 2.0-licensed versions of Elasticsearch and Kibana (version 7.10.2) to create the OpenSearch project. OpenSearch is maintained as a truly open-source project under the Apache 2.0 license, guaranteeing it remains free to use, modify, and distribute without commercial restrictions. This fundamental difference in licensing philosophy is the primary driver behind the decision to choose one over the other.

Both OpenSearch and Elasticsearch are built on the powerful Apache Lucene library, and as such, they share a foundational architecture of nodes, clusters, indices, and shards. Initially, OpenSearch was a near-perfect clone, but by 2026, with OpenSearch versions like 3.x and Elasticsearch versions like 9.x, the two projects have visibly diverged. While the core REST APIs for indexing and searching retain some conceptual similarity, unique features, data structures, and optimizations have led to growing incompatibility at the API and data layer.

Elasticsearch has focused on building a tightly integrated stack with proprietary features, even in its free 'Basic' tier. This includes advanced security, machine learning capabilities (e.g., vector search, anomaly detection), and observability tools that are part of the core distribution. OpenSearch has developed its own open-source alternatives for these functions, such as its Security plugin for access control, Anomaly Detection, and Observability tools. The key difference is that OpenSearch's features are modular plugins under a permissive license, whereas many of Elastic's advanced features are proprietary code, often requiring paid subscriptions for full functionality.

Performance is a nuanced topic for both engines, as it heavily depends on the specific workload, hardware, and configuration. Given their shared Lucene core, both offer exceptional performance and horizontal scalability for a wide range of search, logging, and analytics tasks. Benchmarks often produce conflicting results, with each engine claiming advantages in different scenarios and versions (e.g., OpenSearch 3.x vs. Elasticsearch 9.x).

Elastic, with its single-vendor commercial focus, often optimizes performance for its integrated, proprietary features and its Elastic Cloud managed service. OpenSearch, backed by a broader community including major cloud providers, focuses on generalized performance improvements and optimizations that benefit a wider array of self-hosted and managed environments. For specialized tasks like vector search, performance differences between Elastic's proprietary implementation and OpenSearch's k-NN plugin can be a deciding factor, with each project continuously innovating in these areas.

Elasticsearch boasts the mature, well-known Elastic Stack, which includes Beats, Logstash, and Kibana. It's a cohesive, single-vendor ecosystem with extensive documentation, commercial support, and a dedicated cloud platform (Elastic Cloud). The community is large, but the project's direction is firmly controlled by Elastic NV, with a clear roadmap for proprietary feature development.

OpenSearch has built its own parallel ecosystem, including OpenSearch Dashboards (a fork of Kibana), Data Prepper for data ingestion, and a growing suite of open-source plugins. Its primary strength is its community and vendor-neutral governance. It is supported by a wide range of companies, most notably AWS, which provides Amazon OpenSearch Service. This results in a more federated ecosystem but also offers greater freedom from vendor lock-in and a guarantee that the core project will remain open source, fostering broader community contributions.

Choose Elasticsearch if your organization values a single, commercially supported vendor for your entire observability and search stack. It's the right choice if you need the latest proprietary features developed by Elastic (e.g., advanced security, specific ML capabilities) and are comfortable with the SSPL/Elastic License terms, which primarily restrict your ability to offer a competing hosted service. You benefit from a unified roadmap and commercial support directly from the creators.

Choose OpenSearch if a commitment to permissive, OSI-approved open-source software (Apache 2.0) is a mandate for your team or company. It is the superior choice for avoiding vendor lock-in, retaining the freedom to use and modify the software for any purpose, and leveraging a managed service from a variety of cloud providers beyond just the original creator. OpenSearch offers a robust, community-driven alternative that ensures long-term open-source viability and flexibility.