EmergentDB vs Qdrant
EmergentDB
emergentdb.com
Qdrant
qdrant.techSide by side
| Figure | EmergentDB | Qdrant |
|---|---|---|
| Price from | $2/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 5 | 5 |
| Spec score · Vector Databases | 8.4 (#5) | 8.0 (#9) |
| Product | EmergentDB is an open-source, self-hosted vector database licensed under AGPL-3.0. | Qdrant is a vector similarity search engine with an API to store, search, and manage vectors with additional payload data. |
| Support | The Community plan includes community support. | The pricing page lists community support as Discord-only and paid support options with 10h/day business-hours or 24/7 coverage. |
Plans
EmergentDB
- CommunityFree
- Launch$24 a year
- Launch$29 a month
- Scale$66 a year
- Scale$79 a month
Qdrant
- Free TierFree
- Hybrid CloudPriced on request
- Premium TierPriced on request
- Private CloudPriced on request
- Standard TierPriced on request
In their own words
EmergentDB
EmergentDB is an open-source, self-hosted vector database under the AGPL-3.0 license, also available as managed cloud. It automatically selects a search strategy for a dataset, without requiring manual tuning. Vector insertion and search are available through REST API endpoints; vectors can also be inserted with the TypeScript SDK, using embeddings from any source. Listed index types are Flat, HNSW, IVF, PQ, and Emergent, and SDK languages include TypeScript and Python. The free Community plan includes unlimited vectors, queries, and writes, plus community support and the Bolt-lite engine. Managed Launch is listed at $24 per year, billed annually, with a 500K-vector limit; Scale is $66 per year, billed annually, with a 2.5M-vector limit and dedicated instance. The site lists ISO 27001, SOC 2 Type II, GDPR, HIPAA-ready status, and US, EU, and Asia-Pacific data residency. It also reports a crash-safe write-ahead log and performance figures for specified workloads.
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.