Best VectorDB 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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Build vector search and hybrid search with Elasticsearch's open source vector database — from the leaders in BM25 text search. Try Elasticsearch's vector database, free....
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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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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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Solve AI hallucinations. Vectorize powers accurate, real-time AI agents & RAG pipelines with all your organizational data, including complex documents.
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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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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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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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Build powerful AI applications with Supabase Vector. Store, query, and index vector embeddings using Postgres and Supabase's AI toolkit.
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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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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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Save hundreds of hours wrangling vector data and thousands in embedding costs.The universal vector database management system.
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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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Build on the only database that allows you to transact, analyze and contextualize your data in real time.
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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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Video-based AI memory library. Store millions of text chunks in MP4 files with lightning-fast semantic search. No database needed.
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A multi-modal database that provides multi-modal strong consistency data storage such as relationships, vectors, and text, and provides multi-modal joint analysis capabilities based on SQL
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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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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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ApertureDB: Simplify multimodal AI data. Fast vector search, knowledge graphs, data augmentation. Build smarter AI applications faster.
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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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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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pgvectorscale builds on pgvector with higher performance embedding search and cost-efficient storage for AI applications.
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Low code enterprise data platform for transformation, embedding and vector database load.
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AgentDB: Instant, serverless database for AI applications. Scale autonomous agents with zero-setup provisioning, built-in vector search & optimized costs.
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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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Vald: A scalable, high-performance AI search engine for recommendation systems, translation, and image recognition tasks. Automate indexing and enhance search capabilities with Vald.
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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.
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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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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.