These tools competes with
Redis VectorvsQdrant
In-memory vector search built into Redis — no separate DB needed versus High-performance vector DB with filtering
Compare interactively in Explore →Choose Redis Vector when…
- •already using Redis in your stack
- •need sub-millisecond vector search latency
- •want vector search without adding another infrastructure component
Choose Qdrant when…
- •You need high-performance vector search in production
- •You want OSS with Rust-level performance
- •Filtering alongside vector search is important
Side-by-side comparison
Field
Redis Vector
Qdrant
Category
LLM Infrastructure
LLM Infrastructure
Type
Open Source
Open Source
Free Tier
✓ Yes
✓ Yes
Pricing Plans
OSS: FreeRedis Cloud: From $7/mo
Cloud: Usage-based
GitHub Stars
⭐ 23,000
⭐ 20,000
Health
●95 — Active
●95 — Active
Redis Vector
Redis Vector Search adds native vector similarity search to Redis, enabling low-latency semantic search on data already in Redis. With Redis Stack, you get vector indexing, hybrid search, and filtering alongside your existing caching and pub/sub workloads.
Shared Connections1 tools both integrate with
Only Redis Vector (1)
Qdrant
Only Qdrant (13)
LangGraphLangChainLlamaIndexHaystackDifyVercel AI SDKChromaPineconeWeaviateMilvus
Explore the full AI landscape
See how Redis Vector and Qdrant fit into the bigger picture — 235 tools, 543 relationships, all mapped.