OpenSearch 3.0 released with GPU & vector search
On May 6, 2025, the OpenSearch Software Foundation announced the general availability of OpenSearch 3.0, introducing significant enhancements in vector search performance and scalability.
A key feature of this release is the GPU-accelerated vector indexing, utilising NVIDIA's cuVS technology. This experimental capability delivers up to a 9.3x increase in indexing speed and reduces operational costs by approximately 3.75x, addressing the growing demands of AI applications that rely on processing vast amounts of vector data.
OpenSearch 3.0 also introduces native support for the Model Context Protocol (MCP), facilitating seamless integration between AI agents and the OpenSearch platform. This enhancement enables more comprehensive and customisable AI-powered solutions.
Additional improvements in this release include support for gRPC for efficient data transport, pull-based ingestion from streaming systems like Apache Kafka and Amazon Kinesis, and the integration of Apache Calcite for intuitive query building. These advancements position OpenSearch 3.0 as a robust, open-source solution for organisations seeking scalable and efficient search and analytics capabilities in the era of AI-driven applications.
📰 Who Should Care About the OpenSearch 3.0 News?
📰 Who Should Care About the OpenSearch 3.0 News?
2. Data architects and ML ops teams working with high-dimensional vector data
3. Tech leads and solution architects exploring scalable, open-source alternatives to proprietary search stacks
4. CTOs in AI-driven product companies or platforms handling real-time user queries, recommendations, or semantic search
💡 What You Should Do
💡 What You Should Do
If you're a technology leader evaluating performance improvements in your AI search pipelines or scalable indexing strategies, OpenSearch 3.0 is worth investigating, especially if you're using or planning to use vector search, GPUs, or streaming data ingestion.
Especially those in fintech, SaaS, and data-intensive industries, should explore how this release could reduce infrastructure costs and improve performance. If you're working with CoderTrove or considering outsourcing your DevOps or platform engineering, ask about how your search architecture can benefit from OpenSearch 3.0 and GPU acceleration.
It's a smart moment to benchmark what you're currently using and consider whether open-source, AI-ready upgrades are on your roadmap.
🚀 About Coder Trove — DevOps & Engineering Teams That Scale with You
🚀 About Coder Trove — DevOps & Engineering Teams That Scale with You
At Coder Trove, we help tech-driven companies build high-performance engineering and DevOps teams fast. From AI-ready infrastructure to search optimisation and vector database integration, our experts are already deploying the latest innovations like OpenSearch 3.0, GPU-accelerated indexing, and scalable streaming architectures.
💼 What We Deliver:
1. Augmenting devOps teams fluent in search systems, MLOps, and cloud-native tooling
2. Project-based or embedded engineers for AI/ML and platform support
3. Flexible resourcing for everything from infrastructure upgrades to production-scale deployments
Scale smarter. Build faster. Work with the team that speaks your stack.