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Tools/AutoGen vs Graphiti
AutoGen

AutoGen

framework
vs
Graphiti

Graphiti

framework

AutoGen vs Graphiti — Comparison

Overview
What each tool does and who it's for

AutoGen

Based on the limited social mentions available, AutoGen appears to be recognized as one of the established AI agent frameworks in a competitive landscape that includes LangGraph, CrewAI, and others. Users seem to acknowledge it as part of the mainstream options when evaluating multi-agent systems, though the mentions suggest the space is rapidly evolving with new frameworks emerging frequently. There's an indication that debugging and observability remain challenging aspects of working with AutoGen and similar multi-agent frameworks. However, the provided data is too limited to assess specific user strengths, complaints, pricing sentiment, or overall satisfaction with AutoGen.

Graphiti

Build Real-Time Knowledge Graphs for AI Agents. Contribute to getzep/graphiti development by creating an account on GitHub.

Based on the provided content, there are no reviews or social mentions specifically about "Graphiti." All the social media mentions are about GitHub Copilot, Figma, npm registry tools, and other development-related topics, but none reference a tool called "Graphiti." Without actual user feedback about Graphiti, I cannot provide a meaningful summary of user sentiment, strengths, complaints, or pricing opinions for this specific tool.

Key Metrics
—
Avg Rating
—
1
Mentions (30d)
33
56,499
GitHub Stars
24,254
8,492
GitHub Forks
2,403
34
npm Downloads/wk
—
174,093
PyPI Downloads/mo
—
Community Sentiment
How developers feel about each tool based on mentions and reviews

AutoGen

0% positive100% neutral0% negative

Graphiti

0% positive100% neutral0% negative
Pricing

AutoGen

Graphiti

per-seat + tiered
Use Cases
When to use each tool

Graphiti (1)

Quick Start
Features

Only in Graphiti (10)

Build context graphs that evolve with every interaction — tracking what's true now and what was true before.Give agents rich, structured context instead of flat document chunks or raw chat history.Query across time, meaning, and relationships with hybrid retrieval (semantic + keyword + graph traversal).Python 3.10 or higherNeo4j 5.26 / FalkorDB 1.1.2 / Kuzu 0.11.2 / Amazon Neptune Database Cluster or Neptune Analytics Graph + Amazon OpenSearch Serverless collection (serves as the full text search backend)OpenAI API key (Graphiti defaults to OpenAI for LLM inference and embedding)Google Gemini, Anthropic, or Groq API key (for alternative LLM providers)Connecting to a Neo4j, Amazon Neptune, FalkorDB, or Kuzu databaseInitializing Graphiti indices and constraintsAdding episodes to the graph (both text and structured JSON)
Developer Ecosystem
7,713
GitHub Repos
11
116,169
GitHub Followers
417
20
npm Packages
13
40
HuggingFace Models
—
—
SO Reputation
—
Pain Points
Top complaints from reviews and social mentions

AutoGen

cost tracking (1)

Graphiti

No data yet

Product Screenshots

AutoGen

No screenshots

Graphiti

Graphiti screenshot 1Graphiti screenshot 2Graphiti screenshot 3
Company Intel
information technology & services
Industry
information technology & services
2
Employees
6,000
—
Funding
$7.9B
—
Stage
Other
Supported Languages & Categories

AutoGen

Graphiti

AI/MLFinTechDevOpsSecurityAnalytics
View AutoGen Profile View Graphiti Profile