KDB.AI vs Qdrant
KDB.AI
kdb.ai
Qdrant
qdrant.techSide by side
| Figure | KDB.AI | Qdrant |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 5 |
| Spec score · Vector Databases | 7.9 (#11) | 8.0 (#9) |
| Spec score · Ai Databases | 7.9 (#18) | 8.0 (#14) |
| Deployment | The maker documents both a managed cloud Starter Edition and a self-managed Server Standard Edition. | Qdrant can be run locally using its Docker image or used through Qdrant Cloud. |
| Founded | 1993 | 2021 |
| Headquarters | Newry, Northern Ireland, UK | Berlin, Germany |
| Integrations | The documentation lists LangChain, Vector IO, and LlamaIndex integrations. | Qdrant lists integrations including LangChain, LlamaIndex, Airbyte, Unstructured, DocArray, and AutoGen. |
| Product | KDB.AI is a vector database and search engine for building AI applications with real-time data. | Qdrant is a vector similarity search engine with an API to store, search, and manage vectors with additional payload data. |
| Support | The cloud FAQ directs users to the Slack community or [email protected] for assistance. | The pricing page lists community support as Discord-only and paid support options with 10h/day business-hours or 24/7 coverage. |
Plans
KDB.AI
- KDB.AI Cloud Starter EditionFree
- KDB.AI Server Standard EditionPriced on request
Qdrant
- Free TierFree
- Hybrid CloudPriced on request
- Premium TierPriced on request
- Private CloudPriced on request
- Standard TierPriced on request
In their own words
KDB.AI
KDB.AI is a vector database and search engine for building AI applications with real-time data. Its hybrid search combines dense and sparse vector search with metadata filtering and temporal similarity search. It supports retrieval-augmented generation using unstructured text, video, audio, and image data. Listed vector indexes include Flat, qFlat, IVF, IVFPQ, HNSW, qHNSW, and BM25. Documentation lists integrations with LangChain, Vector IO, and LlamaIndex, while native NVIDIA cuVS integration enables GPU-accelerated vector search. Deployment options include a managed Cloud Starter Edition and a self-managed Server Standard Edition. The free Cloud Starter Edition provides 4 GB of memory per instance, 30 GB of storage, and a 10 MB query size. Its agreement makes no commitment to availability or uptime and provides the service without warranty. The cloud FAQ points users to a Slack community or [email protected] for assistance. The maker presents research assistants, portfolio management, real-time alpha and beta extraction, and image processing as use cases. KDB.AI is offered through API, web, and self-hosted platforms.
Qdrant
Qdrant is a vector similarity search engine and API for storing, searching, and managing vectors with payload data. A point can pair a vector with JSON metadata that filters search results. It supports dense, sparse, and multivector configurations, plus hybrid retrieval that combines semantic and lexical search. These capabilities can serve semantic search and recommendation systems. Qdrant can run locally with its Docker image or through Qdrant Cloud. REST and gRPC APIs are available, along with official client libraries for Python, JavaScript/TypeScript, Rust, Go, .NET, and Java. Listed integrations include LangChain, LlamaIndex, Airbyte, Unstructured, DocArray, and AutoGen. The free cloud tier is intended for testing and prototypes, with a single-node cluster, 1GB RAM, and 4GB disk. Qdrant Cloud enables TLS and encryption at rest; self-hosted users must configure these controls, and authentication and encryption are off by default in self-hosted open-source deployments. Qdrant was founded in 2021 and is headquartered in Berlin, Germany.