OpenSearch Review, Pricing & Features

OpenSearch review covering search, analytics, observability and vector search features, self-hosted and AWS managed pricing, and alternatives to Elasticsearch.

Category
Databases
Pricing
Open Source, from Free
Verified
Not yet
Last updated
July 19, 2026
Founded
2021
Headquarters
San Francisco, California, USA (Linux Foundation)
APIOpen SourceAISelf-Hosted

Overview

OpenSearch is a distributed search and analytics engine that started life as an AWS-led fork of Elasticsearch and Kibana in 2021, created after Elastic changed those projects' licenses away from Apache 2.0. Since September 2024 it has been governed independently by the OpenSearch Software Foundation under the Linux Foundation, with AWS, SAP, and Uber as premier members.

It is used for full-text search, log and metrics analytics, security analytics, and vector search, with OpenSearch Dashboards providing the visualization and exploration layer, functionally similar to Kibana.

Key Features

OpenSearch bundles features that are typically paywalled in competing products, including role-based access control, SAML/LDAP authentication, alerting, anomaly detection, and machine learning plugins, all under the permissive Apache 2.0 license.

Its k-NN vector search plugin supports embedding-based similarity search, making it a common choice for AI-powered search and retrieval-augmented generation pipelines, alongside its established use in log analytics and observability stacks.

Pricing

OpenSearch itself is free and open source with no licensing fees for self-hosting on your own infrastructure.

Organizations that want a managed experience typically pay for Amazon OpenSearch Service or OpenSearch Serverless on a usage basis (compute, storage, and data transfer), or use third-party managed hosting from vendors such as Aiven, DigitalOcean, or Instaclustr, whose pricing varies by provider and cluster size.

Key Features

Pros & Cons

Pros

  • Free under Apache 2.0 with enterprise security features included, unlike Elastic's paywalled model
  • Governed by a neutral, multi-vendor foundation rather than a single company
  • Largely API-compatible with Elasticsearch, easing migration
  • Strong and improving vector search capability for AI and RAG use cases
  • Large download base and active contributor community

Cons

  • Some newer Elasticsearch features diverge and are not available in OpenSearch
  • Managed hosting costs on AWS can scale up significantly with data volume
  • Smaller third-party ecosystem and fewer integrations than Elasticsearch at times
  • Migrating existing Elasticsearch clusters can require compatibility testing
  • Documentation and tooling maturity can lag behind Elastic's commercial offerings

Pricing

Frequently Asked Questions

Is OpenSearch free?

Yes, OpenSearch is free and open source under the Apache 2.0 license; costs only apply if you use a managed hosting service such as Amazon OpenSearch Service.

Who governs OpenSearch?

Since September 2024, OpenSearch has been governed by the OpenSearch Software Foundation, an open technical project within the Linux Foundation, with AWS, SAP, and Uber as premier members.

Why was OpenSearch created?

AWS created OpenSearch in 2021 as a fork of the last Apache 2.0 versions of Elasticsearch and Kibana after Elastic relicensed those projects under the Server Side Public License.

Is OpenSearch compatible with Elasticsearch?

OpenSearch shares a common codebase origin with Elasticsearch and remains largely API-compatible for many operations, though the two projects have diverged over time.

Does OpenSearch support vector search?

Yes, its k-NN plugin supports vector embeddings and similarity search, and the project is actively developing GPU acceleration for large-scale vector workloads.

What is OpenSearch Dashboards?

It is OpenSearch's built-in visualization and analytics interface, functionally equivalent to Kibana, used to explore logs, metrics, and search results.

What are the main alternatives to OpenSearch?

The main alternatives are Elasticsearch, Apache Solr, Algolia, Meilisearch, and Typesense.

Comparisons

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