are widely used for managing, analyzing, and visualizing large-scale data. However, their differences have become more pronounced since Amazon introduced OpenSearch as a fork of Elasticsearch version 7.10. Below is a comparison of the two based on several key aspects:
1. Needs and Features
- Elasticsearch:
- Features a rich ecosystem, including full-text search, data analytics, machine learning, and Elastic APM.
- Well-suited for large-scale data analytics, log search, and observability.
- Designed with a focus on user experience, integrated with Kibana.
- OpenSearch:
- As a fork of Elasticsearch, OpenSearch retains many features of Elasticsearch version 7.10.
- OpenSearch Dashboards replaces Kibana as a data visualization tool.
- Offers flexibility to the open-source community with additional transparent features from Amazon.
2. Ease of Use
- Elasticsearch:
- Comprehensive official documentation and integrated tools like Kibana make it easy to learn.
- Abundant tutorials and user communities make it beginner-friendly.
- OpenSearch:
- Documentation is continuously evolving, supported by the open-source community.
- OpenSearch Dashboards has an interface similar to Kibana but requires adaptation for Elasticsearch users.
3. Pricing and Licensing
- Elasticsearch:
- Uses the “Elastic License,” which imposes certain restrictions, especially for commercial use without approval.
- Commercial service costs vary depending on the features used.
- OpenSearch:
- Licensed under Apache 2.0, which is completely free and open for commercial use.
- A cost-effective solution, especially for organizations avoiding additional licensing fees.
4. Integration
- Elasticsearch:
- Supports integration with various tools like Logstash, Beats, and other observability systems.
- Its ecosystem is highly mature with numerous official plugins.
- OpenSearch:
- Supports integration with tools compatible with Elasticsearch version 7.10.
- Includes additional integration features developed by the community and Amazon.
5. Performance
- Elasticsearch:
- Optimized for high performance in search and data analytics.
- The search engine is regularly updated with the latest technologies.
- OpenSearch:
- Built on the same foundation as Elasticsearch version 7.10, delivering comparable performance.
- Driven by community development to improve scalability.
6. Security
- Elasticsearch:
- Offers security features like Single Sign-On (SSO) and role-based access control in its premium version.
- OpenSearch:
- Provides similar security features for free, including user-based authentication and data encryption.
7. Support and Documentation
- Elasticsearch:
- Official support from Elastic Co., with premium support options.
- Highly detailed documentation for both developers and end users.
- OpenSearch:
- Community-based support and assistance from Amazon Web Services (AWS).
- Documentation is continuously updated, though not as comprehensive as Elasticsearch’s.
8. Testimonials and Reviews
- Elasticsearch:
- Praised for its performance, but some criticism has emerged regarding its licensing changes, which limit user flexibility.
- OpenSearch:
- Appreciated as a robust, cost-free alternative.
- Well-received by the community for offering greater freedom in usage and development.
Comparison Table
| Aspect | Elasticsearch | OpenSearch |
|---|---|---|
| Needs and Features | Full-text search, analytics, APM, ML | Similar to Elasticsearch 7.10, transparent |
| Ease of Use | Comprehensive documentation, official tutorials | Growing documentation, Kibana adaptation |
| Pricing and Licensing | Elastic License, premium features are paid | Free, Apache 2.0 |
| Integration | Supports many tools in the Elastic ecosystem | Compatible with Elasticsearch 7.10 tools |
| Performance | High performance, regularly updated | Comparable to Elasticsearch 7.10 |
| Security | Premium security features | Free security features |
| Support | Official support from Elastic Co. | Community support and AWS |
| Testimonials | Positive for features, criticized for licensing | Positive for usage freedom |
Author’s Perspective
From the author’s perspective, choosing between OpenSearch and Elasticsearch depends largely on user needs and project objectives. Elasticsearch remains the go-to option for users seeking the latest features and official support from Elastic Co. However, for organizations prioritizing flexibility, cost savings, and unrestricted usage, OpenSearch stands out as an appealing alternative.
OpenSearch has significant potential, especially with support from the open-source community and AWS. In the long term, OpenSearch could become a more competitive solution if its development remains consistent. Meanwhile, Elasticsearch continues to excel in technological innovation and its mature ecosystem.
