OpenSearch named GigaOm leader in vector databases

OpenSearch has been named a Leader and Fast Mover in GigaOm's 2025 Radar for Vector Databases, placing the project in the Innovation/Platform Play quadrant.

The recognition comes as new industry research points to growing corporate use of hybrid and vector-enabled search systems for generative AI and retrieval-augmented generation applications.

GigaOm highlighted OpenSearch for combining vector search with broader search and analytics capabilities in a single platform. The firm cited support for hybrid search across dense and sparse vectors, scalable indexing, k-nearest neighbour performance, and tools for tuning relevance in real time.

It also noted how the software combines vector retrieval with traditional full-text search, filtering, and aggregations. That mix is being used in enterprise workloads including semantic search, observability, and retrieval-augmented generation.

Market shift

The wider backdrop is a rapid shift in how companies organise search and retrieval for AI projects. Businesses adopting large language models are under pressure to improve the quality of results returned to users and reduce the risk of inaccurate responses. That has increased interest in systems that combine lexical and semantic methods.

According to GigaOm, vector databases can deliver measurable operational gains, with users seeing a 40-60% improvement in search relevance and a 30-50% reduction in infrastructure costs by consolidating systems that have often been deployed separately.

OpenSearch is an open source project overseen by the OpenSearch Software Foundation. The software is intended to let organisations combine vector, semantic, and full-text search in a single stack rather than relying on multiple products for different retrieval tasks.

That idea is also central to a separate report by S&P Global Market Intelligence 451 Research, commissioned by the foundation. It found that organisations using hybrid and vector-augmented search can improve search accuracy and make data retrieval more central to AI initiatives.

Hybrid search

The 451 Research study described hybrid search as the next stage in enterprise search, combining the precision of lexical search with the contextual relevance of semantic search. It reflects a shift away from keyword-only approaches as companies try to extract more useful answers from large and varied data sets.

The same study valued the vector-supported database market at USD $454.4 million in 2024. Analysts expect measured growth in 2025 and 2026, followed by a stronger upward trend from 2027, leading to a projected compound annual growth rate of 49% through 2029.

OpenSearch's market position is also tied to its open source model. Supporters of open source search infrastructure argue that it gives buyers more control over data architecture and supplier relationships at a time when AI software stacks are becoming more complex and expensive to manage.

GigaOm made that case directly in its assessment. "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, GigaOm. "Vector database platforms like OpenSearch are positioned as foundational infrastructure driving AI maturity, operational agility, and competitive differentiation across industries."

The foundation said the recognition aligns with what it is hearing from users adopting AI search systems. It said demand centres on openness, flexibility, and the ability to support production environments without forcing organisations into closed technology stacks.

"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, 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."

The latest analyst reports suggest vector databases are moving from specialist tools into a broader enterprise software category, driven by demand for more reliable AI outputs and better search relevance. For OpenSearch, the GigaOm ranking places the project among the vendors and platforms seeking to benefit from that shift.