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  • A real-time vector database for AI applications offering fast similarity search, scalable indexing, and embeddings management.
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    What is eigenDB?
    eigenDB is a purpose-built vector database tailored for AI and machine learning workloads. It enables users to ingest, index, and query high-dimensional embedding vectors in real time, supporting billions of vectors with sub-second search times. With features such as automated shard management, dynamic scaling, and multi-dimensional indexing, it integrates via RESTful APIs or client SDKs in popular languages. eigenDB also offers advanced metadata filtering, built-in security controls, and a unified dashboard for monitoring performance. Whether powering semantic search, recommendation engines, or anomaly detection, eigenDB delivers a reliable, high-throughput foundation for embedding-based AI applications.
    eigenDB Core Features
    • Real-time similarity search
    • Scalable vector indexing
    • RESTful API access
    • Client SDKs for Python and JavaScript
    • Metadata filtering and hybrid search
    • Enterprise-grade security controls
    • Automated shard management
    • Unified monitoring dashboard
    eigenDB Pro & Cons

    The Cons

    No information about pricing or enterprise features
    No direct mobile or browser extension support
    Limited information on scalability and real-world deployment cases

    The Pros

    Highly performant and fast in-memory vector database
    Lightweight and written in Go for efficiency
    Supports similarity search using HNSW algorithm
    Simple REST API for easy integration
    Open-source with an active development community
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