Best Elasticsearch's vector database Alternatives in 2025
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Use managed or self-hosted vector databases to give LLMs the ability to work on YOUR data & context.
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VectorDB is a simple, lightweight, fully local, end-to-end solution for using embeddings-based text retrieval.
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Vearch: Hybrid vector search database. Combine similarity & scalar filters for precise AI results. Scale effortlessly. Python/Go SDKs.
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Discover the client-vector-search library: embed, store, search, and cache vectors effortlessly. Enhance your applications with efficient vector search capabilities.
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PGVecto.rs is a Postgres extension that enables scalable vector search, allowing you to build powerful similarity-based applications on top of your Postgres database.
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SvectorDB allows you to set up a serverless vector database in under 120 seconds, perfect for RAG chatbots, document search, and recommendations.
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Build powerful AI applications with Supabase Vector. Store, query, and index vector embeddings using Postgres and Supabase's AI toolkit.
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LanceDB: Blazing-fast vector search & multimodal data lakehouse for AI. Unify petabyte-scale data to build & train production-ready AI apps.
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Supercharge your AI applications with Zilliz's Milvus vector database. Deploy and scale your vector search apps hassle-free with Zilliz Cloud.
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Elastic Search AI Platform. Advanced search meets generative AI. Boost security, optimize operations. Scale with flexibility. Try free trial!
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Discover Milvus, the popular vector database for enterprise users. Store, index, and manage large-scale embedding vectors with ease. Boost retrieval speed and create similarity search services using Milvus' advanced SDKs and indexing algorithms. Perfect for machine learning deployments and managing large-scale vector datasets.
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VectorChord is a high-performance PostgreSQL extension for vector similarity search. Enhanced speed, scalability & affordability. Ideal for e-commerce, research & media.
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Solve AI hallucinations. Vectorize powers accurate, real-time AI agents & RAG pipelines with all your organizational data, including complex documents.
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TopK is a cloud-native database intended for search use cases. It comes with keyword search, vector search, and metadata filtering built-in.
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pgvectorscale builds on pgvector with higher performance embedding search and cost-efficient storage for AI applications.
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HelixDB is a high-performance database system designed with a focus on developer experience and efficient data operations. Built in Rust and powered by LMDB as its storage engine, it combines the reliability of a proven storage layer with modern features tailored for AI and vector-based applications.
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pgvector: An open-source vector similarity search tool for Postgres. Store vectors with data, support exact & approximate search, and perform distance calculations. Suitable for recommendation systems, image/text retrieval, and anomaly detection.
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Save hundreds of hours wrangling vector data and thousands in embedding costs.The universal vector database management system.
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Discover how Analytics to Elevate Semantic Search can optimize embedded documents, improve search results, and enhance user experiences.
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Enable every developer to build production-grade GenAI applications with powerful and familiar SQL. Minimal Learning, Max Value, and Cost-Effective.
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Pinecone is the leading AI infrastructure for building accurate, secure, and scalable AI applications. Use Pinecone Database to store and search vector data at scale, or start with Pinecone Assistant to get a RAG application running in minutes.
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OceanBase seekdb is an open-source, AI-native search database that unifies relational, vector, text, JSON and GIS in a single engine, enabling hybrid search and in-database AI workflows.
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Discover the power of SemaDB, the low-cost, high-performance vector database for AI applications. Uncover hidden connections and enhance your search experience with natural language interaction.
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Infinity is a cutting-edge AI-native database that provides a wide range of search capabilities for rich data types such as dense vector, sparse vector, tensor, full-text, and structured data. It provides robust support for various LLM applications, including search, recommenders, question-answering, conversational AI, copilot, content generation, and many more RAG (Retrieval-augmented Generation) applications.
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Qdrant is a vector database for storing, searching, and managing high - dimensional vectors. It offers efficient storage, fast similarity search, scalability, and rich API. Ideal for AI, ML, and NLP applications. Click to learn more!
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FastEmbed is a lightweight, fast, Python library built for embedding generation. We support popular text models. Please open a Github issue if you want us to add a new model.
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Build on the only database that allows you to transact, analyze and contextualize your data in real time.
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Lantern is a Postgres vector database that is scalable, cost-effective, and easy to use
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Superlinked is a Python framework for AI Engineers building high-performance search & recommendation applications that combine structured and unstructured data.
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Weaviate: The open source vector database powering AI apps. Fast vector search with structured filters. Flexible, scalable, production-ready for developers.