OpenSearch 3.0 augments vector database performance, search infrastructure, and more

The OpenSearch Software Foundation, the vendor-neutral home for the OpenSearch Project, is releasing OpenSearch 3.0, delivering a 9.5x performance improvement over OpenSearch 1.3, building on benchmarking data that showed earlier iterations of OpenSearch operating 1.6x faster than its closest industry competitor.

According to the vendor, OpenSearch 3.0 enables users to increase efficiency, deliver superior performance, and accelerate AI application development via new data management, AI agent, and vector search capabilities.

“The enterprise search market is skyrocketing in tandem with the acceleration of AI, and it is projected to reach $8.9 billion by 2030,” said Carl Meadows, governing board chair at the OpenSearch Software Foundation and director of product management at Amazon Web Services (AWS). “OpenSearch 3.0 is a powerful step forward in our mission to support the community with an open, scalable platform built for the future of search and analytics, and it reflects our commitment to open collaboration and innovation that drives real-world impact.”

To support its large-scale search platform and manage a vast amount of vector data, OpenSearch introduced GPU-based acceleration, leveraging NVIDIA cuVS for indexing workflows.

New vector engine features include:

• GPU Acceleration for OpenSearch Vector Engine: Delivers superior performance for large-scale vector workloads while significantly lowering operational spend by reducing index building time.
• Model Context Protocol (MCP) Support: Native MCP support allows AI agents to easily communicate with OpenSearch, enabling more comprehensive and customizable AI-powered solutions.
• Derived Source: Reduces storage consumption by one-third by removing redundant vector data sources and utilizing primary data to recreate source documents as needed for reindexing or source call back.

OpenSearch 3.0 provides major advancements in how the platform ingests, transports, and manages data including:

• Support for gRPC
• Pull-based Ingestion
• Reader and Writer Separation
• Apache Calcite Integration
• Index Type Detection

Enhancements to the platform's search infrastructure—removing legacy code, adopting a modular architecture and aligning with the latest Java advancements—boosts maintainability, performance potential, and efficiency. Updates include:

• Lucene 10 Upgrade
• Java 21 Minimum Supported Runtime
• Java Platform Module System Support

OpenSearch 3.0 is now available.

For more information about this news, visit https://opensearch.org.