When it comes to search engines, OpenSearch and Elasticsearch are two of the most popular options. Both are based on Apache Lucene and provide powerful full-text search, analytics, and logging capabilities. However, OpenSearch and Elasticsearch have evolved in different directions over time, particularly after a pivotal split in 2021.
If you’re deciding between OpenSearch and Elasticsearch for your project, it’s essential to understand the key differences between them. In this post, we’ll break down these differences, compare their features, and guide you on how to choose the right tool for your use case.
What Are OpenSearch and Elasticsearch?
Before diving into the differences, let’s briefly define each technology.
- Elasticsearch: Elasticsearch is an open-source search and analytics engine developed by Elastic. It allows you to store, search, and analyze large volumes of data in real-time. Elasticsearch is a core component of the Elastic Stack (formerly known as the ELK Stack), which includes other tools like Logstash (data processing) and Kibana (data visualization).
- OpenSearch: OpenSearch is an open-source search and analytics suite that was created as a fork of Elasticsearch 7.10 after Elastic changed the licensing for Elasticsearch. OpenSearch is managed by the OpenSearch community under the governance of Amazon Web Services (AWS), and it includes features similar to Elasticsearch but with a focus on open-source development and community contributions.
Key Differences Between OpenSearch and Elasticsearch
1. Licensing and Governance
One of the most significant differences between OpenSearch and Elasticsearch is their licensing models and governance.
- Elasticsearch (Elastic Stack): Starting with version 7.11, Elasticsearch transitioned to a Server Side Public License (SSPL), which is not considered an open-source license by the Open Source Initiative (OSI). This change led to concerns in the open-source community about the long-term openness of Elasticsearch.
- OpenSearch: OpenSearch is fully Apache 2.0 licensed, meaning it remains fully open-source and free to use, modify, and distribute. OpenSearch is also community-driven and governed by a diverse set of stakeholders, including AWS and other contributors.
Why This Matters:
- If you’re looking for a fully open-source solution without any restrictions or concerns about licensing, OpenSearch is the better choice.
- If you are already using Elasticsearch 7.10 or earlier, you can continue using it under the Apache 2.0 license, but anything beyond that may require a commercial license depending on your usage.
2. Development and Feature Roadmaps
Since the split in 2021, the development roadmaps for OpenSearch and Elasticsearch have diverged.
- Elasticsearch: Elasticsearch continues to be developed by Elastic, which focuses on adding features tied to its commercial offerings. While the core Elasticsearch engine remains open-source, certain advanced features—such as machine learning, security, and alerting—are only available in paid versions. Elastic’s focus is on integrating Elasticsearch with its broader enterprise tools like Kibana, APM, and Elastic Security.
- OpenSearch: OpenSearch is community-driven and focuses on remaining fully open-source with no proprietary features locked behind a paywall. OpenSearch has adopted a more inclusive development process, with features like advanced security, alerting, and distributed tracing built into the core. OpenSearch’s roadmap is community-centric, ensuring that its features remain open and free.
Why This Matters:
- If you require enterprise features (e.g., machine learning, alerting, security) with a commercial support plan, Elasticsearch may be the better choice. However, if you prefer an entirely open-source ecosystem with no lock-in, OpenSearch will likely meet your needs.
3. Compatibility and Ecosystem
While OpenSearch and Elasticsearch are based on the same codebase up to version 7.10, their compatibility has diverged since the fork. Here are some key points:
- Elasticsearch: Elastic continues to release new versions of Elasticsearch with additional features and updates. However, some of these updates (like proprietary features) are only available with Elastic’s commercial offerings.
- OpenSearch: OpenSearch started as a fork of Elasticsearch 7.10 and retains compatibility with that version. Since then, OpenSearch has added new features and improvements, but it does not include proprietary functionality from Elastic. OpenSearch is also designed to be compatible with Kibana via OpenSearch Dashboards, a fork of Kibana.
Why This Matters:
- If you’re already using Elasticsearch 7.10 or earlier and want to continue with similar functionality, OpenSearch is fully compatible.
- If you plan to adopt new features in Elasticsearch (particularly those tied to Elastic’s commercial offerings), you might need to stick with Elasticsearch.
4. Community Support and Ecosystem
- Elasticsearch: Elastic has a large commercial organization behind Elasticsearch, which provides professional support, training, and consulting. Elastic also offers additional commercial tools, such as Elastic APM, Elastic Observability, and Elastic Security, to extend the capabilities of Elasticsearch.
- OpenSearch: OpenSearch is governed by the OpenSearch community, with contributions from a wide variety of organizations, including AWS, as well as individual developers. Community support is strong, and OpenSearch benefits from a collaborative development process. OpenSearch also offers OpenSearch Dashboards as a visualization layer, similar to Kibana, for analyzing and visualizing your data.
Why This Matters:
- If you need enterprise support, professional services, or a comprehensive commercial stack, Elasticsearch is the way to go.
- If you prefer an open-source ecosystem with community-driven support and development, OpenSearch is a great choice.
5. Performance and Scalability
Both OpenSearch and Elasticsearch are designed to handle large-scale search and analytics workloads with high availability, fault tolerance, and real-time performance. However, since the two projects have diverged, their performance optimizations may vary slightly.
- Elasticsearch: As part of Elastic’s commercial stack, Elasticsearch offers some performance optimizations, particularly around integrations with other Elastic tools, which might offer an edge in certain enterprise environments.
- OpenSearch: OpenSearch has a focus on open-source optimization, ensuring that performance improvements and enhancements are accessible to everyone. The community-driven model allows for quicker adoption of performance-enhancing features like better compression, more efficient sharding, and indexing improvements.
Why This Matters:
- Both platforms are highly scalable and optimized for large-scale workloads. However, OpenSearch may be a better option for users who want to take advantage of cutting-edge optimizations in a purely open-source context.
6. Security Features
- Elasticsearch: Elastic provides security features like encryption, role-based access control (RBAC), and audit logging, but these are only available in the commercial offerings (Elastic Stack with a subscription).
- OpenSearch: OpenSearch includes security features like encryption, authentication, RBAC, and audit logging as part of the core distribution. These features are fully open-source, giving users access to essential security controls without needing a commercial license.
Why This Matters:
- If you need security features built into your search engine without a subscription, OpenSearch is the better choice, as it includes security features as part of the core package.
- Elasticsearch’s security features are tied to commercial licenses, which could be an important consideration if you are already using Elastic’s commercial stack.
Choosing the Right Tool: OpenSearch vs. Elasticsearch
Now that we’ve explored the key differences, let’s consider which tool might be right for you.
Choose OpenSearch if:
- You prefer a fully open-source solution with no proprietary features or licensing concerns.
- You want community-driven development and support, with a focus on open-source innovation.
- You need built-in security, alerting, and monitoring capabilities without additional licensing fees.
- You’re looking for a cost-effective solution without vendor lock-in.
Choose Elasticsearch if:
- You need enterprise-grade features like machine learning, security, and observability, and are willing to pay for them.
- You are already using the Elastic Stack and want to leverage other Elastic products like APM, Kibana, and Elastic Security.
- You require commercial support and professional services for mission-critical applications.
Conclusion
Both OpenSearch and Elasticsearch are powerful search engines with many similarities, but their differences—particularly in licensing, governance, and feature availability—make each better suited to different use cases. If you prioritize openness, community-driven development, and a fully free and open ecosystem, OpenSearch is the ideal choice. On the other hand, if you require enterprise features and professional support from a vendor, Elasticsearch remains a robust and reliable option.
In the end, choosing the right tool depends on your specific needs, your team’s requirements, and your preferences for open-source vs. commercial solutions. Happy searching!