Best Vector Databases
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Compare the Top Vector Databases as of April 2025
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What are Vector Databases?
Vector databases are a type of database that use vector-based data structures, rather than the traditional relational models, to store information. They are used in artificial intelligence (AI) applications such as machine learning, natural language processing and image recognition. Vector databases support fast and efficient data storage and retrieval processes, making them an ideal choice for AI use cases. They also enable the integration of structured and unstructured datasets into a single system, offering enhanced scalability for complex projects. Compare and read user reviews of the best Vector Databases currently available using the table below. This list is updated regularly.
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MongoDB Atlas
MongoDB
The most innovative cloud database service on the market, with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. MongoDB Atlas is the global cloud database service for modern applications. Deploy fully managed MongoDB across AWS, Google Cloud, and Azure with best-in-class automation and proven practices that guarantee availability, scalability, and compliance with the most demanding data security and privacy standards. The best way to deploy, run, and scale MongoDB in the cloud. MongoDB Atlas offers built-in security controls for all your data. Enable enterprise-grade features to integrate with your existing security protocols and compliance standards. With MongoDB Atlas, your data is protected with preconfigured security features for authentication, authorization, encryption, and more.Starting Price: $0.08/hour -
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CrateDB
CrateDB
The enterprise database for time series, documents, and vectors. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source distributed database running queries in milliseconds, whatever the complexity, volume and velocity of data.
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