These tools competes with

QdrantvsRedis Vector

High-performance vector DB with filtering versus In-memory vector search built into Redis — no separate DB needed

Compare interactively in Explore →

Choose Qdrant when…

  • •You need high-performance vector search in production
  • •You want OSS with Rust-level performance
  • •Filtering alongside vector search is important

Choose Redis Vector when…

  • •already using Redis in your stack
  • •need sub-millisecond vector search latency
  • •want vector search without adding another infrastructure component

Side-by-side comparison

Field
Qdrant
Redis Vector
Category
LLM Infrastructure
LLM Infrastructure
Type
Open Source
Open Source
Free Tier
✓ Yes
✓ Yes
Pricing Plans
Cloud: Usage-based
OSS: FreeRedis Cloud: From $7/mo
GitHub Stars
⭐ 20,000
⭐ 23,000
Health
●80 — Active
●80 — Active

Qdrant

Rust-based vector database optimized for filtering. Supports named vectors, payloads, and hybrid search. Self-hostable or cloud.

Website ↗GitHub ↗

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.

Website ↗GitHub ↗

Shared Connections1 tools both integrate with

pgvector

Only Qdrant (11)

LangGraphLangChainLlamaIndexHaystackDifyChromaWeaviateMilvusPineconeVercel AI SDK

Only Redis Vector (1)

Qdrant

Explore the full AI landscape

See how Qdrant and Redis Vector fit into the bigger picture — 207 tools, 452 relationships, all mapped.

Open in Explore →