These tools integrates with

Mem0vsQdrant

Universal persistent memory layer for AI agents versus High-performance vector DB with filtering

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Choose Mem0 when…

  • You want your AI agent to remember users and preferences across sessions
  • You need a universal memory layer that works with any LLM or framework
  • You're building personalized AI assistants with long-term context

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
Mem0
Qdrant
Category
Memory & Persistence
LLM Infrastructure
Type
Open Source
Open Source
Free Tier
✓ Yes
✓ Yes
Pricing Plans
Pro: $49/mo
Cloud: Usage-based
GitHub Stars
30,000
20,000
Health
85 Active
95 Active

Mem0

Open-source persistent memory layer that gives AI agents the ability to remember users, preferences, and context across sessions. Supports vector, graph, and key-value storage backends. AWS partner for Strands Agents. YC W23, $24M raised, 30K+ GitHub stars.

Qdrant

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

Shared Connections1 tools both integrate with

Only Mem0 (5)

ZepOpenAI APIQdrantCogneeGraphiti

Only Qdrant (13)

LangChainLlamaIndexHaystackDifyVercel AI SDKChromaPineconepgvectorWeaviateMilvus

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See how Mem0 and Qdrant fit into the bigger picture — 235 tools, 543 relationships, all mapped.

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