If you’re building a system for log analytics, application search, or security monitoring, you’ve almost certainly faced a critical decision: OpenSearch vs Elasticsearch. For years, Elasticsearch was the undisputed king, but since 2021, its open-source fork, OpenSearch, has emerged as a powerful and popular alternative. What began as a dispute over licensing has evolved into two distinct projects with different philosophies, features, and performance characteristics.
Choosing between them is no longer a simple matter. It’s a strategic decision that impacts everything from your budget and licensing compliance to your system’s performance and future scalability. As we move through 2025, the paths of these two search engines have diverged enough that making an informed choice is more important than ever. This guide breaks down the key differences to help you decide which platform is right for your needs.
A Shared Heritage: Where OpenSearch and Elasticsearch Align
Before diving into the differences, it’s important to remember that OpenSearch is a fork of Elasticsearch version 7.10.2. Because of this shared DNA, their core functionalities are very similar. Both are:
- Built on Apache Lucene: They use the same powerful, high-performance search library at their core.
- Distributed and Scalable: Both are designed to scale horizontally across multiple nodes, handling massive volumes of data.
- RESTful API-driven: They share a familiar and comprehensive REST API for indexing, searching, and managing data.
- Versatile: Both are excellent choices for a wide range of use cases, including full-text search, log analytics, security information and event management (SIEM), and business analytics.
For basic search and analytics tasks, you’ll find a familiar experience with either tool. However, the moment you look beyond the basics, the differences become clear.
Key Differences: How the Paths Have Diverged
The 2021 fork was a turning point. Since then, Elastic N.V. (the company behind Elasticsearch) and the AWS-led OpenSearch project have been innovating on separate tracks. Let’s compare the key areas where they now differ.
The Licensing Divide: The Fork’s Origin Story
The single most significant difference between the two projects is their licensing, which was the very reason for the fork.
- Elasticsearch: Starting with version 7.11, Elasticsearch moved to a dual-license model: the Server Side Public License (SSPL) and the Elastic License. The SSPL is not considered a true open-source license by the Open Source Initiative (OSI). It includes a clause requiring anyone who offers Elasticsearch as a managed service to release the source code of their entire management stack. This move was designed to prevent cloud providers like AWS from offering a managed Elasticsearch service without a commercial agreement with Elastic.
- OpenSearch: In response, AWS forked the last Apache 2.0 licensed version of Elasticsearch. OpenSearch remains under the permissive Apache 2.0 license, which is a true, OSI-approved open-source license. It allows anyone to use, modify, and distribute the software for any purpose with very few restrictions.
The takeaway: If your organization has a strict policy requiring the use of OSI-approved open-source software, OpenSearch is your only option. For others, the choice depends on whether the SSPL’s restrictions affect your use case.
Features & Development Pace
When Amazon created OpenSearch, it had to remove all of Elastic’s proprietary X-Pack code. This meant early versions of OpenSearch lacked features like alerting, machine learning, and advanced security. The OpenSearch project has since been adding these capabilities back through a plugin-based architecture.
- Elasticsearch continues to innovate at a rapid pace, tightly integrating new features into the core product. This includes powerful capabilities in vector search, security analytics, and observability, often released first and more deeply integrated than in OpenSearch. Development is centralized and driven by Elastic.
- OpenSearch development is led by AWS and a community of partners. Its focus has been on building a robust plugin ecosystem and deep integration with AWS services. For example, instead of the original X-Pack features, you use the OpenSearch Observability plugin, machine learning plugins, and connectors to services like Amazon S3 and Kinesis.
The visualization tools are also forks: Elasticsearch uses Kibana, while OpenSearch uses OpenSearch Dashboards. While they started from the same codebase, their user experiences are now diverging, with many users noting that Kibana’s UI feels more polished.
The Performance Question: Benchmarking Speed and Efficiency
Performance is a critical factor, especially at scale. Recent third-party and internal benchmarks have shown a growing performance gap between the two.
- Search Analytics: A study by TechTarget’s Enterprise Strategy Group found that for common log analytics workloads (text querying, sorting, date histograms), Elasticsearch was 40-140% faster than OpenSearch while using fewer compute resources.
- Vector Search: With the rise of AI, vector search performance is crucial. In a 2024 performance analysis published by Elastic, Elasticsearch proved to be 2x to 12x faster than OpenSearch for vector search operations.
Elastic attributes this lead to its deep investment in optimizing Apache Lucene specifically for these use cases, whereas the OpenSearch project has taken a broader approach by integrating multiple search libraries. If raw performance is your top priority, current data suggests Elasticsearch has a significant edge.
Security: Included vs Tiered
The approach to security features is a major point of differentiation and a significant factor in cost.
- OpenSearch: A key advantage of OpenSearch is that it includes a comprehensive suite of security features for free. This includes fine-grained access control (role-based, document-level, and field-level security), audit logging, and encryption in transit.
- Elasticsearch: The free Basic tier of Elasticsearch includes foundational security features like password protection and TLS encryption. However, more advanced features like role-based access control (RBAC), field-level security, and audit logging are reserved for paid subscription tiers (Gold, Platinum, or Enterprise).
The takeaway: If you need advanced security but are on a tight budget, OpenSearch offers a more complete package out of the box.
Pricing & Managed Services
While both projects are free to download and self-manage, most users opt for a managed service to avoid the operational overhead of running a large distributed system.
- Amazon OpenSearch Service: This is the flagship managed offering for OpenSearch. It uses a pay-per-use pricing model fully integrated with AWS billing and offers a generous free tier, making it very accessible to get started.
- Elastic Cloud: This is Elastic’s official managed service. It is available on AWS, Google Cloud, and Microsoft Azure. Pricing is based on a tiered subscription model (Standard, Gold, Platinum, Enterprise) that starts at a higher baseline price but includes integrated support and access to all advanced features depending on the tier.
For self-hosted deployments, OpenSearch is completely free. Elasticsearch is also free, but the SSPL license may have implications for commercial use, and you won’t have access to the premium features without a subscription.
So, Which One Should You Choose in 2025?
The “better” choice in the OpenSearch vs Elasticsearch debate depends entirely on your organization’s priorities. There is no single right answer, only the right fit for your use case.
Choose Elasticsearch if:
- Peak performance is your priority: For the fastest possible query speeds, especially for vector search and log analytics, benchmarks show Elasticsearch is the clear leader.
- You want the latest, most integrated features: Elastic’s rapid, centralized development means you often get access to cutting-edge capabilities first.
- You prefer a single vendor for software and support: Elastic Cloud offers a tightly integrated experience with support directly from the creators of the software.
- The SSPL license is not a blocker for your organization’s policies or business model.
Choose OpenSearch if:
- A true, permissive open-source license (Apache 2.0) is a non-negotiable requirement.
- You need advanced security features without a premium subscription: The free, comprehensive security suite is a major advantage.
- You are deeply integrated into the AWS ecosystem: Amazon OpenSearch Service offers seamless integration with other AWS services like Kinesis, S3, and Lambda.
- Cost-effectiveness is a primary driver: The pay-per-use model and generous free tier make it easier to start small and control costs.
Ultimately, the decision requires a careful evaluation of your technical needs, budget constraints, and philosophical stance on software licensing. Both are powerful, capable search engines, but they now serve different visions of what a search and analytics platform should be.
No matter which engine you choose, ensuring its health and performance is crucial. Monitoring your cluster’s resource usage, query latency, and indexing rates is essential for maintaining a responsive and reliable service.
Get started with Netdata for free today to gain real-time, high-granularity insights into your entire infrastructure, including your Elasticsearch or OpenSearch clusters.