GigaOm Radar for Vector Databases v3 Positions Vespa.ai as a Leader and Outperformer

Vespa Recognized for Integrated Ranking, Multimodal Search, and Production-Scale AI Performance

TRONDHEIM, Norway--(BUSINESS WIRE)--Vespa.ai, the creator of the AI Search Platform for building and deploying large-scale, real-time AI applications powered by big data, today announced its recognition as a Leader and Outperformer in the GigaOm Radar for Vector Databases v3, marking the company’s third consecutive year being evaluated in GigaOm’s vector database research.

Now in its third edition, the report compares 17 leading open source and commercial solutions using GigaOm’s structured evaluation framework. In addition to core table-stakes capabilities, the Radar reviews each vendor’s key features, emerging strengths, and broader business criteria. The shift from Sonar to Radar reflects the technology’s transition into mainstream adoption.

GigaOm names Vespa.ai a leader for its ability to manage complex data, optimize results at scale, and support multimodal AI workloads. The report highlights Vespa’s native tensor support, efficient retrieval across sparse and dense vectors, and integrated ranking pipeline for delivering highly relevant answers in real time. GigaOm also notes Vespa’s strength in handling varied data types, including text, images, and multi-vector embeddings, making it well-suited for large-scale AI search and RAG applications.

Andrew Brust, Analyst, GigaOm: “Vespa.ai was classified as an Outperformer because of its proficiency in storing, retrieving, and processing complex data structures at scale and in real time.”

Jon Bratseth, CEO and Founder, Vespa. “We’re pleased to be named a leader as vector technologies enter mainstream use. GigaOm’s report highlights a key point: vector storage alone doesn’t deliver meaningful results. At scale, organizations need integrated ranking, efficient retrieval pipelines, and the ability to work across different data types. That’s why many teams come to Vespa after discovering the limits of standalone vector stores and the complexity of stitching together additional ranking or filtering services. Vespa was built to handle these challenges in one system, and it’s encouraging to see GigaOm recognize the importance of this unified approach.”

The GigaOm Radar for Vector Database can be downloaded here:
https://content.vespa.ai/gigaom-report-v3-2025

About Vespa

Vespa.ai is an AI Search Platform designed for large-scale Retrieval-Augmented Generation (RAG), recommendation, and personalization systems, enabling AI services to deliver accurate and relevant answers. By unifying data, inference, and ranking within a single query path, Vespa provides real-time performance across massive datasets with high throughput and low latency. Offered as a managed service, Vespa supports mission-critical workloads for leading organizations including Perplexity, Spotify, and Yahoo.