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eigenDB Product Information

What is eigenDB?

eigenDB is a specialized vector database engineered for AI and machine learning applications. It allows users to store, index, and query high-dimensional embedding vectors in real time, scaling to billions of vectors with sub-second search performance. The platform features automated shard management, dynamic scaling, and multi-dimensional indexing, accessible through RESTful APIs or client SDKs in popular programming languages. Additional capabilities include advanced metadata filtering, built-in security controls, and a unified dashboard for performance monitoring. Whether enabling semantic search, recommendation systems, or anomaly detection, eigenDB provides a robust, high-throughput foundation for embedding-driven AI solutions.

Who will use eigenDB?

  • AI Developers
  • Machine Learning Engineers
  • Data Scientists
  • Product Managers
  • Enterprise Architects

How to use the eigenDB?

  • Step 1: Sign up for an eigenDB account via the Mintlify dashboard.
  • Step 2: Create a new vector database instance and configure your region settings.
  • Step 3: Ingest embedding vectors using the REST API or the Python/JavaScript SDK.
  • Step 4: Define your index parameters and metadata fields for filtering.
  • Step 5: Execute similarity searches or hybrid queries through the API endpoints.
  • Step 6: Monitor usage, latency, and throughput in the eigenDB dashboard.
  • Step 7: Integrate the search results into your application for production deployment.

Platform

  • Web
  • macOS
  • Windows
  • Linux

eigenDB's Core Features & Benefits

The 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

The Benefits

  • Sub-second retrieval at massive scale
  • Supports billions of vectors
  • Easy integration with SDKs
  • Automatic performance optimization
  • Secure access and role-based management

eigenDB's Main Use Cases & Applications

  • Semantic document search for knowledge bases
  • Personalized product recommendation engines
  • Image and video similarity retrieval
  • Anomaly detection in time-series data
  • Contextual chatbot response retrieval

eigenDB's Pros & Cons

The Pros

High-performance, fast in-memory vector database

Lightweight and built in Go for efficiency

Supports similarity search with the HNSW algorithm

Simple REST API for straightforward integration

Open-source with an active developer community

The Cons

Pricing and enterprise feature details are not publicly available

No direct support for mobile or browser extensions

Limited information on scalability and real-world deployment examples

FAQs of eigenDB

What is eigenDB?

eigenDB is a purpose-built vector database for storing, indexing, and searching high-dimensional embeddings to power AI applications.

How do I ingest data into eigenDB?

You can ingest embeddings using the RESTful API or the official Python and JavaScript SDKs.

Which programming languages are supported?

eigenDB offers official SDKs for Python and JavaScript, along with a universal REST API for other languages.

How does eigenDB handle scaling?

eigenDB employs automated shard management and dynamic scaling to maintain consistent performance as your data volume increases.

What security features does eigenDB offer?

It provides role-based access control, encryption for data at rest and in transit, and comprehensive audit logging.

What is the pricing model?

Pricing is based on usage, factoring in stored vectors, query volume, and data transfer. Check the pricing page for specific details.

Can I self-host eigenDB?

No, eigenDB is a fully managed service provided by Mintlify and is not available for self-hosting.

How can I monitor performance?

Use the integrated eigenDB dashboard to monitor latency, throughput, and resource usage in real time.

How do I apply metadata filters in searches?

Add metadata filter parameters to your query payload to refine vector search results based on specific attributes.

Does eigenDB support hybrid search?

Yes, eigenDB supports hybrid search, combining vector similarity with keyword or metadata filtering.

eigenDB Company Information

eigenDB Screenshot

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