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ElasticsearchComparisonBeginner · 4 min read

Elasticsearch vs OpenSearch: Key Differences and When to Use Each

Both Elasticsearch and OpenSearch are powerful search and analytics engines based on Apache Lucene. Elasticsearch is developed by Elastic with a proprietary license, while OpenSearch is a community-driven fork under the Apache 2.0 license, offering similar core features but with open governance.
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Quick Comparison

Here is a quick side-by-side comparison of Elasticsearch and OpenSearch on key factors.

FactorElasticsearchOpenSearch
LicenseElastic License (proprietary)Apache 2.0 (open source)
GovernanceElastic company controlledCommunity-driven with AWS support
CompatibilityLatest versions may break compatibilityForked from Elasticsearch 7.10, mostly compatible
FeaturesIncludes proprietary features like machine learningFocuses on open features, some proprietary removed
Community & SupportCommercial support from ElasticCommunity and AWS support
Release FrequencyRegular updates with new featuresIndependent updates, slower but stable
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Key Differences

Elasticsearch is developed and maintained by Elastic, which changed its license to a proprietary Elastic License starting from version 7.11. This means some features and code are no longer open source, and usage restrictions apply. In contrast, OpenSearch was created as a fork of Elasticsearch 7.10 under the Apache 2.0 license, ensuring it remains fully open source and free to use.

The governance model differs significantly: Elasticsearch is controlled by Elastic, which decides the roadmap and features, while OpenSearch is community-driven with contributions from AWS and others, promoting open collaboration. This affects how quickly new features appear and how the projects evolve.

Feature-wise, Elasticsearch offers advanced proprietary capabilities like machine learning, alerting, and security features in its commercial tiers. OpenSearch focuses on maintaining core search and analytics features without proprietary extensions, aiming for transparency and open development.

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Code Comparison

Here is how you create an index and add a document in Elasticsearch using its REST API.

json
PUT /my-index
{
  "settings": {
    "number_of_shards": 1
  },
  "mappings": {
    "properties": {
      "title": { "type": "text" },
      "date": { "type": "date" }
    }
  }
}

POST /my-index/_doc/1
{
  "title": "Hello Elasticsearch",
  "date": "2024-01-01"
}
Output
{ "acknowledged": true, "shards_acknowledged": true, "index": "my-index" } { "_index": "my-index", "_id": "1", "result": "created" }
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OpenSearch Equivalent

The same index creation and document insertion in OpenSearch uses the same REST API syntax, ensuring compatibility.

json
PUT /my-index
{
  "settings": {
    "number_of_shards": 1
  },
  "mappings": {
    "properties": {
      "title": { "type": "text" },
      "date": { "type": "date" }
    }
  }
}

POST /my-index/_doc/1
{
  "title": "Hello OpenSearch",
  "date": "2024-01-01"
}
Output
{ "acknowledged": true, "shards_acknowledged": true, "index": "my-index" } { "_index": "my-index", "_id": "1", "result": "created" }
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When to Use Which

Choose Elasticsearch if you need advanced proprietary features, official commercial support, and the latest innovations from Elastic. It suits enterprises requiring machine learning, alerting, and security features integrated tightly.

Choose OpenSearch if you prefer a fully open source solution with an Apache 2.0 license, want community-driven development, or need to avoid vendor lock-in. It is ideal for users who want stable core search and analytics without proprietary restrictions.

Key Takeaways

Elasticsearch uses a proprietary license with advanced commercial features, while OpenSearch is fully open source under Apache 2.0.
OpenSearch is a community-driven fork of Elasticsearch 7.10, maintaining compatibility and open governance.
Both support similar core APIs, making migration or dual usage straightforward for basic search tasks.
Choose Elasticsearch for enterprise features and official support; choose OpenSearch for open source freedom and community collaboration.