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
●80 — Active
●80 — 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 (11)
LangGraphLangChainLlamaIndexHaystackDifyChromaWeaviateMilvusPineconeVercel AI SDK
Explore the full AI landscape
See how Redis Vector and Qdrant fit into the bigger picture — 207 tools, 452 relationships, all mapped.