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Tools/Graphiti vs Streamlit
Graphiti

Graphiti

framework
vs
Streamlit

Streamlit

framework

Graphiti vs Streamlit — Comparison

Overview
What each tool does and who it's for

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.

Streamlit

Streamlit is an open-source Python framework for data scientists and AI/ML engineers to deliver interactive data apps – in only a few lines of code.

Based on the limited social mentions provided, Streamlit appears to be gaining attention in the AI and data visualization space, with users leveraging it for rapid prototyping of data dashboards and intelligence platforms. The mentions suggest developers are using Streamlit to build sophisticated tools like news intelligence platforms and dashboard generators within very short timeframes (as little as 3 days). Users seem to appreciate Streamlit's ability to quickly transform data science projects into shareable web applications. However, without detailed reviews or pricing discussions in the provided content, it's difficult to assess user sentiment regarding costs, specific complaints, or comprehensive strengths.

Key Metrics
—
Avg Rating
—
33
Mentions (30d)
1
24,254
GitHub Stars
44,071
2,403
GitHub Forks
4,179
—
npm Downloads/wk
—
—
PyPI Downloads/mo
—
Community Sentiment
How developers feel about each tool based on mentions and reviews

Graphiti

0% positive100% neutral0% negative

Streamlit

0% positive100% neutral0% negative
Pricing

Graphiti

per-seat + tiered

Streamlit

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)

Only in Streamlit (10)

Share your apps with the whole worldPublic apps onlyTotally freeCode in your browser or favorite editorWork with Git and CI/CDEnterprise-grade securityDeploy with Streamlit Community CloudDeploy with SnowflakeNeil TreatGoogle X
Developer Ecosystem
11
GitHub Repos
108
417
GitHub Followers
4,702
13
npm Packages
20
—
HuggingFace Models
40
—
SO Reputation
—
Product Screenshots

Graphiti

Graphiti screenshot 1Graphiti screenshot 2Graphiti screenshot 3

Streamlit

Streamlit screenshot 1
Company Intel
information technology & services
Industry
information technology & services
6,000
Employees
35
$7.9B
Funding
$862.0M
Other
Stage
Merger / Acquisition
Supported Languages & Categories

Graphiti

AI/MLFinTechDevOpsSecurityAnalytics

Streamlit

AI/MLDevOpsSecurityAnalyticsDeveloper Tools
View Graphiti Profile View Streamlit Profile