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Letta vs Weaviate

LettaWeaviate

Bottom line: Letta for teams that need persistent agent memory; Weaviate for teams wanting open-source flexibility plus managed option.

LettaLetta

Stateful AI agents with long-term memory (formerly MemGPT).

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WeaviateWeaviate

Open-source AI-native vector database

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Votes00
PricingFreemiumFreemium
CategoryCodingCoding
Tags
agentsmemoryopen-sourcestateful-agentsllm-framework
vector-databaseopen-sourceraghybrid-searchsemantic-search
Best for
  • Teams that need persistent agent memory
  • Builders of long-running assistants
  • Researchers exploring stateful agents
  • Teams wanting open-source flexibility plus managed option
  • RAG and hybrid search applications
  • Organizations avoiding vendor lock-in
Pros
  • Purpose-built for the agent memory problem
  • Strong research pedigree (MemGPT paper)
  • OS-style tiered memory persists across sessions
  • Open-source core, free to self-host
  • Managed Letta Cloud with free and paid tiers
  • Open source with the option to self-host for free
  • Managed Weaviate Cloud with a free sandbox
  • Built-in vectorizer and generative (RAG) modules
  • Strong hybrid search and metadata filtering
  • Multi-tenancy and replication for production
Cons
  • Narrower than general agent frameworks
  • Often used alongside other tooling, not a full stack
  • Renamed from MemGPT, some older docs use old name
  • Cloud pricing and tiers still evolving
  • Python-focused
  • Larger configuration surface than minimalist DBs
  • Module system adds a learning curve
  • Managed pricing by vector dimensions can be unintuitive
  • Self-hosting production clusters requires ops effort
  • Resource-hungry at large scale

Comparison generated from each tool's listing. Add or remove tools above to change it.