8 Best Graphiti Alternatives in 2026 (Open Source)
Graphiti — Build Real-Time Knowledge Graphs for AI Agents. Builds temporal graphs that track what's true now and what was true before, unlike static knowledge graphs.
These 8 open-source tools do the same job. They are ordered by how closely they match Graphiti, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| Graphiti(original) | 31.3k | +2,611 | 2026-09-30 |
| Memary | 2.7k | +12 | 2024-10-18 |
| Cognee | 31.2k | +2,656 | 2026-09-29 |
| MemOS | 11.7k | +972 | 2026-09-22 |
| OpenViking | 39.1k | +3,255 | 2026-09-30 |
| GraphRAG | 36.2k | +3,015 | 2026-09-23 |
| LightRAG | 39.9k | +3,328 | 2026-09-26 |
| Supermemory | 31.0k | +2,587 | 2026-09-30 |
| Graphify | 122.8k | +10,231 | 2026-09-30 |
1. Memary
The Open Source Memory Layer For Autonomous Agents
What sets it apart: vs LangChain Memory / Mem0: graph-database-backed memory system emulating human memory (breadth + depth tracking) — agents automatically build and query knowledge graphs rather than flat conversation history
Best for: Building persistent, context-aware AI agents with evolving memory; User preference tracking and personalization across sessions; Multi-user agent management with separate knowledge contexts
2. Cognee
Knowledge Engine for AI Agent Memory in 6 lines of code
What sets it apart: Unlike Mem0 (conversation memory) or Chroma (pure vector search), Cognee builds an evolving knowledge graph from documents, combining vector + graph search with cognitive science approaches, ontology grounding, and cross-agent knowledge sharing — making it AI memory infrastructure rather than just a vector database.
Best for: AI agent developers who need persistent, learning memory that combines vector search with knowledge graph relationships; Enterprise use cases requiring tenant isolation, audit trails, and cross-agent knowledge sharing
3. MemOS
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harne
What sets it apart: Provides a unified memory operating system with graph-structured memory that's inspectable and editable, not just a black-box embedding store.
Best for: AI agents needing long-term memory; multi-agent collaboration systems; developers building context-aware agents
4. OpenViking
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
What sets it apart: Organizes agent context as an inspectable virtual filesystem with URI addresses instead of a black-box embedding store.
Best for: Developers needing structured agent memory; Projects requiring inspectable and editable agent knowledge; Teams wanting a unified filesystem for agent context
5. GraphRAG
A modular graph-based Retrieval-Augmented Generation (RAG) system
What sets it apart: Uses knowledge graph memory structures rather than traditional vector search for enhanced LLM context retrieval.
Best for: enhancing LLM reasoning with private data; creating structured knowledge graphs from documents; research projects exploring graph-based RAG
6. LightRAG
[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation
What sets it apart: Combines simple RAG implementation with advanced features like knowledge graphs, multimodal processing, and comprehensive evaluation tooling.
Best for: developers building RAG-powered agents; multimodal document processing; knowledge-intensive agent applications
7. Supermemory
Memory and context engine + app that is extremely fast, scalable, and can be run fully locally. The Memory API for the AI era.
What sets it apart: Claims #1 performance on three major AI memory benchmarks with 95% recall and 99.4% context reduction.
Best for: Adding persistent memory to AI agents; Building AI products with memory capabilities; Running memory systems locally
8. Graphify
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini
What sets it apart: Uses deterministic AST parsing to create an explainable knowledge graph locally, without vector stores or embeddings, specifically for AI coding workflows.
Best for: Developers using AI coding assistants; Understanding complex codebases; Navigating project documentation and relationships
FAQ
- What are the best alternatives to Graphiti?
- The closest open-source alternatives to Graphiti are Memary, Cognee and MemOS, followed by OpenViking, GraphRAG and LightRAG. They are ranked by how closely they match what Graphiti does.
- Which Graphiti alternative is the most popular?
- Graphify has the most GitHub stars among Graphiti alternatives, with 122,766 stars.
- Which Graphiti alternative is the most actively maintained?
- By recent activity, Cognee (2,437 commits in the last 90 days) is the most actively developed alternative.