- Home
- Vector Databases
- KDB.AI
KDB.AI
Newry, Northern Ireland, UK
What it is
KDB.AI is a vector database and search engine for building AI applications with real-time data. Its hybrid search combines dense and sparse vectors with metadata filtering and temporal similarity search. The platform supports retrieval-augmented generation using text, video, audio, and image data. Documented indexes include Flat, qFlat, IVF, IVFPQ, HNSW, qHNSW, and BM25, while listed integrations include LangChain, Vector IO, and LlamaIndex. Native NVIDIA cuVS integration supports GPU-accelerated vector search. KDB.AI offers a managed cloud Starter Edition and a self-managed Server Standard Edition, with API, web, and self-hosted platforms. The free Cloud Starter Edition provides 4 GB memory per instance, 30 GB storage, and a 10 MB query size. The agreement makes no commitment to uptime or availability and provides the service without warranty. Support is available through Slack or [email protected]. The maker presents research assistants, portfolio management, real-time alpha and beta extraction, and image processing as use cases.
For and against
For
- Free cloud plan is available
- Hybrid search supports dense and sparse vectors
- Metadata and temporal similarity search are supported
- Works with text, video, audio, and images
- Offers managed and self-managed deployment
Against
- Starter Edition limits storage to 30 GB
- Starter queries are limited to 10 MB
- Service agreement makes no uptime commitment
The verdict
KDB.AI provides vector search, multimodal retrieval, and multiple deployment choices, including a free cloud tier. Teams should account for Starter limits and the agreement’s lack of uptime commitment.
Who it suits
KDB.AI suits developers building AI applications that need vector search over real-time or multimodal data. It also fits teams choosing between managed cloud and self-managed deployment.
Plans and prices
KDB.AI Cloud Starter Edition
4 GB memory per instance · 30 GB storage · 10 MB query size
Read 4 Oct 2026 · code.kx.com
KDB.AI Server Standard Edition
Single-container deployment · scale to requirements · customize to development environment
Read 4 Oct 2026 · code.kx.com
On the record
- Availability terms
- The Cloud Starter agreement makes no commitment to service availability or uptime and says the service is provided without warranty.kdb.ai · read 4 Oct 2026
- Deployment
- The maker documents both a managed cloud Starter Edition and a self-managed Server Standard Edition.code.kx.com · read 4 Oct 2026
- GPU integration
- KDB.AI natively integrates NVIDIA cuVS for GPU-accelerated vector search.kdb.ai · read 4 Oct 2026
- Indexes
- The cloud FAQ lists Flat, qFlat, IVF, IVFPQ, HSNW, and qHSNW as supported vector indexes.code.kx.com · read 4 Oct 2026
- Integrations
- The documentation lists LangChain, Vector IO, and LlamaIndex integrations.code.kx.com · read 4 Oct 2026
- Limits
- KDB.AI Cloud Starter Edition provides 4 GB RAM, 30 GB storage, and a 10 MB query size.code.kx.com · read 4 Oct 2026
- Multimodal
- The product supports RAG with unstructured data such as text, video, audio, and images.kdb.ai · read 4 Oct 2026
- Product
- KDB.AI is a vector database and search engine for building AI applications with real-time data.code.kx.com · read 4 Oct 2026
- Search
- It supports hybrid search combining dense and sparse vector search, metadata filtering, and temporal similarity search.kdb.ai · read 4 Oct 2026
- Security terms
- The Cloud Starter agreement asks users to secure their credentials and access keys and notify KX if they suspect compromise.kdb.ai · read 4 Oct 2026
- Support
- The cloud FAQ directs users to the Slack community or [email protected] for assistance.code.kx.com · read 4 Oct 2026
- Use cases
- The maker presents AI research assistants, portfolio management, real-time alpha and beta extraction, and image processing as use cases.kdb.ai · read 4 Oct 2026
