NeMo Guardrails vs Graphiti — Features, Pricing & Reviews Compared

NeMo Guardrails

framework

Graphiti

framework

Overview

What each tool does and who it's for

NeMo Guardrails

We create the world’s fastest supercomputer and largest gaming platform.

NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Credit: Runway AI, Adobe, Tabnine, WPP Credit: WPP, McLaren; Koenigsegg; BMW; Rimac “NVIDIA is reshaping the future of computing. We’ve built a culture where people can do their life's work. We are a learning machine. The mission is boss. Everyone has a voice.” — Jensen Huang

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

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Avg Rating

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Mentions (30d)

5,896

GitHub Stars

24,254

637

GitHub Forks

2,403

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npm Downloads/wk

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PyPI Downloads/mo

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Community Sentiment

How developers feel about each tool based on mentions and reviews

NeMo Guardrails

0% positive100% neutral0% negative

Graphiti

0% positive100% neutral0% negative

Pricing

NeMo Guardrails

tiered

Graphiti

per-seat + tiered

Use Cases

When to use each tool

Graphiti (1)

Quick Start

Features

Only in NeMo Guardrails (10)

NVIDIA GTCData CenterAgentic AIShort DescriptionNVIDIA, T-MobileMake AutonomousBuilding the Future Together post 1NVIDIA Dynamo 1.0 post 2New Open Physical AI GTC26 2L’Oréal Uses post 1

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

707

GitHub Repos

24,153

GitHub Followers

417

npm Packages

HuggingFace Models

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SO Reputation

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Product Screenshots