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Vespa Voice: The Rise of Vector Databases

In this episode, we chat with Whit Walters, Field CTO at GigaOm, and dive into GigaOm’s latest Sonar Report on vector databases, exploring why Vespa.ai is recognized as both a Leader and Fast Mover in the space. We break down what sets Vespa apart—from its integrated architecture that runs data, indices, metadata, and machine learning inferences on the same physical nodes, to its unmatched performance at scale. We explore how Vespa’s support for lexical, vector, and hybrid search methods gives enterprises strategic flexibility in tackling a range of retrieval challenges. With its ability to process hundreds of thousands of queries per second with low latency, Vespa is pushing the boundaries of what’s possible in enterprise-scale AI search. Beyond vectors, we discuss how Vespa’s full-text search, structured filtering, ML-powered ranking, and real-time indexing combine to create a powerful, production-ready stack for next-gen search applications.