Compare the Top Vector Databases that integrate with JSON as of October 2025

This a list of Vector Databases that integrate with JSON. Use the filters on the left to add additional filters for products that have integrations with JSON. View the products that work with JSON in the table below.

What are Vector Databases for JSON?

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 for JSON currently available using the table below. This list is updated regularly.

  • 1
    ApertureDB

    ApertureDB

    ApertureDB

    Build your competitive edge with the power of vector search. Streamline your AI/ML pipeline workflows, reduce infrastructure costs, and stay ahead of the curve with up to 10x faster time-to-market. Break free of data silos with ApertureDB's unified multimodal data management, freeing your AI teams to innovate. Set up and scale complex multimodal data infrastructure for billions of objects across your entire enterprise in days, not months. Unifying multimodal data, advanced vector search, and innovative knowledge graph with a powerful query engine to build AI applications faster at enterprise scale. ApertureDB can enhance the productivity of your AI/ML teams and accelerate returns from AI investment with all your data. Try it for free or schedule a demo to see it in action. Find relevant images based on labels, geolocation, and regions of interest. Prepare large-scale multi-modal medical scans for ML and clinical studies.
    Starting Price: $0.33 per hour
  • 2
    Oracle Autonomous Database
    Oracle Autonomous Database is a fully automated cloud database that uses machine learning to automate database tuning, security, backups, updates, and other routine management tasks traditionally performed by DBAs. It supports a wide range of data types and models, including SQL, JSON documents, graph, geospatial, text, and vectors, enabling developers to build applications for any workload without integrating multiple specialty databases. Built-in AI and machine learning capabilities allow for natural language queries, automated data insights, and the development of AI-powered applications. It offers self-service tools for data loading, transformation, analysis, and governance, reducing the need for IT intervention. It provides flexible deployment options, including serverless and dedicated infrastructure on Oracle Cloud Infrastructure (OCI), as well as on-premises with Exadata Cloud@Customer.
    Starting Price: $123.86 per month
  • 3
    Azure Managed Redis
    Azure Managed Redis features the latest Redis innovations, industry-leading availability, and a cost-effective Total Cost of Ownership (TCO) designed for the hyperscale cloud. Azure Managed Redis delivers these capabilities on a trusted cloud platform, empowering businesses to scale and optimize their generative AI applications seamlessly. Azure Managed Redis brings the latest Redis innovations to support high-performance, scalable AI applications. With features like in-memory data storage, vector similarity search, and real-time processing, it enables developers to handle large datasets efficiently, accelerate machine learning, and build faster AI solutions. Its interoperability with Azure OpenAI Service enables AI workloads to be faster, scalable, and ready for mission-critical use cases, making it an ideal choice for building modern, intelligent applications.
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