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Search/vector database

Full-text, log search, and vector similarity engines.

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20
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20

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Includes evidence-backed assignments to this category and its descendants. Totals describe indexed coverage, not the complete market.

Zilliz offers a fully managed Vector Lakebase powered by Milvus, unifying real-time vector search, lake-scale discovery, and AI data operations. Available across AWS, Google Cloud, and Azure regions worldwide.

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vendors
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customers

Updated Oct 18, 2026

Power insights and outcomes with The Elasticsearch Platform. See into your data and find answers that matter with enterprise solutions designed to help you accelerate time to insight. Try Elastic toda...

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vendors
8
customers

Updated Oct 7, 2026

Welcome to our Trust Center. At Algolia, search is more than a feature—it’s a seamless, intelligent experience. Our AI-powered platform helps teams build fast, intuitive discovery that connects users to what they need in an instant. Every product we build begins with one question: how do we protect what matters? From architecture to interface, security is not added on—it’s built in.

2
vendors
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customers

Updated Oct 5, 2026

Pinecone is the trusted AI knowledge company. Its AI knowledge platform—Database, Nexus, and Marketplace—powers accurate, fast, cost-effective AI for 10,000+ customers and 1M developers worldwide.

10
vendors
4
customers

Updated Oct 5, 2026

Self-tuning file search for AI agents. Captain syncs scanned DOCX, complex PDFs, and video from sources like S3, SharePoint, and Google Drive, and makes complex files searchable with one API call, self-tuned towards your accuracy and latency targets.

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Updated Oct 1, 2026

Moss is building the real-time semantic search runtime for conversational and multimodal AI. Our system enables voice agents, copilots, and chat interfaces to retrieve, reason, and respond in sub-10 ms, delivering the responsiveness that makes AI interactions feel truly natural. If you’ve ever built a conversational or voice AI product, you’ve felt the lag. That moment when an agent pauses and the illusion of intelligence breaks. The bottleneck is almost always retrieval. Each query hops across networks and databases, adding delay and cost. Moss eliminates that gap by keeping retrieval close to where the agent runs. Moss runs natively across browsers, mobile devices, and servers with an optimized vector index built in Rust and WebAssembly. It enables teams to build AI products that feel instant, contextual, and adaptive. The experiences that sustain engagement and unlock new kinds of interaction. For our customers, this translates into tangible business value: stronger user retention, higher conversion, and entirely new product categories made possible by real-time understanding. Moss is already powering production pilots across voice AI and developer platforms, achieving sub-10 ms retrieval and 70–90% token savings compared to traditional pipelines.

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Updated Sep 28, 2026

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