LanceDB vs Qdrant
Compare deployment options, cost efficiency, and features to choose the right vector database for your application.
Database Comparison
LanceDB takes the lead.
Both LanceDB and Qdrant are powerful vector databases designed for efficient similarity search and storage. However, their deployment options and features differ in important ways.
Why LanceDB:
- LanceDB ranks higher overall
- LanceDB is more cost-effective
- LanceDB has 3 more strengths
LanceDB
LanceDB is an open-source, AI-native multimodal lakehouse designed for billion-scale vector search. Built on the Lance columnar format, it combines embedded simplicity with cloud-scale performance. LanceDB's disk-based architecture with compute-storage separation enables up to 100x cost savings compared to memory-based solutions while supporting multimodal data (text, images, video, audio).
Qdrant
Qdrant is an open-source vector database available as both a managed cloud service and a self-hosted solution. It offers strong HNSW performance, flexible deployment, and predictable cost structures, making it suitable for both startups and large-scale RAG workloads.
Feature Comparison
Infrastructure & Technical Details
| Feature | LanceDB | Qdrant |
|---|---|---|
| Deployment | Embedded/Local, Self-Hosted, Managed Cloud (LanceDB Cloud) | Self-Hosted, Managed Cloud |
| Cost | OSS: Free; Cloud: usage-based with $100 free credits; Enterprise: custom pricing | Starts ~$0.014/hour for smallest node |
| License | Apache 2.0 | Apache 2.0 |
| Index Types | IVF-PQ, IVF-HNSW-PQ, BTree | HNSW, Sparse (dot similarity) |
| Cloud Providers | AWS, Azure, GCP, Any (self-hosted) | AWS, Azure, GCP |
| Regional Flexibility | high | high |
| Strengths | 13 | 10 |
| Weaknesses | 9 | 5 |