OpenSearch Named a Leader in GigaOm Radar for Vector Databases as Research Shows Hybrid Search Becomes Critical for AI

New industry research highlights rapid adoption of vector-enabled search infrastructure for generative AI applications

• OpenSearch was named a Leader and Fast Mover in the 2025 GigaOm Radar for Vector Databases, recognizing its production-ready hybrid and vector search capabilities within a unified open source search and analytics platform.
• New research from S&P Global Market Intelligence 451 Research shows enterprises are rapidly adopting hybrid and vector-enabled search infrastructure to power generative AI and retrieval-augmented generation applications while improving search relevance.
• OpenSearch enables organizations to combine vector, semantic and traditional full-text search in a single platform, helping enterprises modernize AI data retrieval while consolidating infrastructure and maintaining control of their technology stack.

AMSTERDAM – KubeCon + CloudNativeCon Europe – 24 March, 2026 – The OpenSearch Software Foundation, the neutral home for the OpenSearch Project, today announced OpenSearch was named a Leader and Fast Mover in the Innovation/Platform Play quadrant in the 2025 GigaOm Radar for Vector Databases v3. This recognition reflects OpenSearch’s mature, production-ready vector search capabilities integrated within a full-featured search and analytics platform.

As generative AI adoption accelerates, organizations are modernizing retrieval infrastructure to support hybrid search and retrieval-augmented generation (RAG) applications. Increasingly, enterprises are investing in vector databases and hybrid search technologies to improve relevance, reduce hallucinations, and consolidate traditionally siloed data infrastructure.

GigaOm Radar Recognizes OpenSearch for Hybrid and Vector Search Innovation

According to GigaOm, vector databases deliver quantifiable operational improvements such as 40-60% enhancement in search relevance and a 30-50% reduction in infrastructure costs through consolidation of traditionally siloed systems. OpenSearch exemplifies these benefits as its vector search platform combines robust full-text and neural vector capabilities with open source flexibility to help build scalable AI applications.

The report highlighted OpenSearch’s support for hybrid search across dense and sparse vectors, scalable indexing and k-NN performance, and flexible relevance tuning to optimize real-time results. GigaOm also noted OpenSearch’s ability to unify vector retrieval with traditional full-text search, filtering, and aggregations, making it well-suited for enterprise AI applications such as semantic search, observability and retrieval-augmented generation (RAG) workloads at scale.

Additionally, OpenSearch’s open source model provides organizations strategic autonomy, eliminating vendor lock-in risk and facilitating continuous innovation through community contributions and extensive integrations with major embedding providers and large language model (LLM) platforms.

“OpenSearch represents a compelling choice by combining proven scalability, comprehensive functionality, and open source economics that reduce risk and enhance innovation velocity,” said Howard Holton, CEO at GigaOm. “Vector database platforms like OpenSearch are positioned as foundational infrastructure driving AI maturity, operational agility, and competitive differentiation across industries.”

From Lexical to Semantic: How Vector Databases Enhance Enterprise Search

The recognition comes as new industry research shows enterprises are rapidly adopting vector-enabled search infrastructure to support AI-driven applications.

A new report from S&P Global Market Intelligence 451 Research, commissioned by OpenSearch Software Foundation, finds that organizations adopting hybrid and vector-augmented search are able to improve search accuracy and transform data retrieval into a strategic capability for AI initiatives.

“Recognition from independent analysts reflects what we’re hearing from organizations across the industry: AI applications require retrieval infrastructure that is open, flexible and built to scale,” said Bianca Lewis, executive director of the OpenSearch Software Foundation. “As hybrid and vector search become foundational to generative AI and retrieval-augmented generation, the OpenSearch community is focused on delivering production ready capabilities that help enterprises modernize search, reduce infrastructure complexity and maintain control of their data and AI stack.”

Highlights from S&P Global’s report include:

• Hybrid search represents the next evolution of search, offering a more accurate and comprehensive approach that combines the precision of lexical search with the contextual relevance of semantic search.
• The vector-supported database market was valued at $454.4 million in 2024, and analysts expect measured growth in 2025 and 2026, followed by a more pronounced upward trend beginning in 2027, for a projected CAGR of 49% through 2029.

Download a copy of the GigaOm Radar for Vector Databases v3, GigaOm CIO Decision Brief: Vector Databases - OpenSearch, and 451 Research Special Report - From Lexical to Semantic: How Vector Databases Enhance Enterprise Search for more information.

The OpenSearch community is gathering at OpenSearchCon Europe in Prague, Czechia from 16-17 April. Register to attend here. To learn more about the OpenSearch Software Foundation, including how to get involved, become a member or contribute, please visit foundation.opensearch.org/.

About the OpenSearch Software Foundation

The OpenSearch Software Foundation is a vendor-neutral community for search, analytics, observability, and vector database software. Hosted by the Linux Foundation and supported by premier members such as AWS, IBM, SAP and Uber, the OpenSearch Software Foundation works with community maintainers, developers, and member organizations to drive the continued growth of the OpenSearch project. With more than 1 billion software downloads since its inception and participation from thousands of contributors, the OpenSearch project and its community are transforming how information is managed and discovered. To learn more, please visit foundation.opensearch.org.

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