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| Elasticsearch vs OpenSearch: A Comprehensive Comparison |
When it comes to search and analytics engines, Elasticsearch and OpenSearch are two of the most prominent solutions available. Both provide powerful features for indexing and querying data at scale, but their differences go beyond their names. In this article, we’ll dive into the origins, features, performance, and community support of Elasticsearch and OpenSearch to help you make an informed choice for your project.
Origins and Background
Elasticsearch was developed by Elastic NV and became one of the most popular open-source tools for distributed search and analytics. It is built on Apache Lucene and offers robust search capabilities, making it widely used in log analytics, full-text search, and application monitoring.
OpenSearch, on the other hand, emerged as a fork of Elasticsearch in 2021 after Elastic changed the licensing of Elasticsearch and Kibana from open-source (Apache 2.0) to the Elastic License. OpenSearch is maintained by the OpenSearch Project, spearheaded by AWS, and remains under the Apache 2.0 license, ensuring its open-source status.
Key Features Comparison
| Feature | Elasticsearch | OpenSearch |
|---|---|---|
| Licensing | Elastic License (proprietary) | Apache 2.0 (open-source) |
| Search Capability | Advanced full-text search and analytics | Similar to Elasticsearch with comparable search features |
| Plugins | Rich ecosystem, but some are proprietary | Fully open-source plugins |
| Security | Native support with paid subscriptions | Built-in and free under Apache 2.0 |
| Community Support | Large community but commercial-focused | Open-source community-driven development |
Performance
Both Elasticsearch and OpenSearch deliver excellent performance for search and analytics tasks, but there are subtle differences:
Indexing Speed:
- Elasticsearch is known for its high-speed indexing, especially when scaling horizontally.
- OpenSearch has similar indexing capabilities, as it inherited much of Elasticsearch's core code.
Query Execution:
- Elasticsearch’s query performance is optimized for advanced use cases, such as machine learning (ML)-powered search.
- OpenSearch matches Elasticsearch in most standard query scenarios and focuses on maintaining compatibility with Elasticsearch’s APIs.
Scalability:
- Both platforms are designed to scale horizontally by adding more nodes to the cluster.
- OpenSearch prioritizes maintaining open standards while scaling efficiently.
Security
Security is a key consideration in any search engine deployment. Here’s how the two compare:
- Elasticsearch: Security features like role-based access control (RBAC) and audit logging are available, but these often require a subscription to Elastic's paid plans.
- OpenSearch: Offers robust security features out of the box, including RBAC, encryption, and audit logging, all included under its Apache 2.0 license.
Ecosystem and Tooling
- Elasticsearch integrates seamlessly with Kibana for visualization, Logstash for data ingestion, and Beats for lightweight data shipping. However, some advanced features in these tools are locked behind Elastic’s commercial offerings.
- OpenSearch provides OpenSearch Dashboards (a Kibana fork) for visualization and has community-supported tools for data ingestion and processing. Its ecosystem is fully open-source.
Community and Future
The future of Elasticsearch is tied to Elastic NV's commercial goals, with a focus on offering a unified platform for observability and security use cases. OpenSearch, however, is guided by an open-source philosophy, making it appealing to developers and organizations prioritizing openness and transparency.
Use Cases
| Use Case | Elasticsearch | OpenSearch |
|---|---|---|
| Log Analytics | Widely used with Elastic Stack | Comparable capabilities via OpenSearch Stack |
| Application Search | Advanced relevance tuning | Similar functionality |
| Observability | Strong ecosystem but with paid features | Fully open-source solutions |
Which One Should You Choose?
Choose Elasticsearch if:
- You are comfortable with proprietary licensing.
- You need access to Elastic's machine learning and advanced observability features.
- You're looking for commercial support directly from Elastic.
Choose OpenSearch if:
- You prioritize open-source software and licensing freedom.
- You want full access to security and analytics features without a paywall.
- You are looking for community-driven innovation.
Both Elasticsearch and OpenSearch are powerful solutions for search and analytics. While Elasticsearch offers a more mature ecosystem, OpenSearch provides a fully open-source alternative with comparable functionality. Your choice should depend on your licensing preferences, budget, and the specific features you require.
For organizations prioritizing cost-efficiency and open-source principles, OpenSearch is a compelling choice. On the other hand, if your project relies heavily on Elastic’s advanced features and commercial support, Elasticsearch remains a strong contender.
By carefully assessing your requirements, you can confidently select the right tool for your search and analytics needs.