Supermemory VS Graphiti

Supermemory

ai second brain for all your saved stuff

Graphiti

Build personalized AI agents that learn from dynamic data

Not present

Analysis of Supermemory

Overall verdict

Supermemory is a solid tool for building a personal or organizational knowledge base, offering an effective way to save, organize, and retrieve information from across the web using AI-powered search and recall.

Why this product is good

AI-powered semantic search lets you retrieve saved content by meaning rather than exact keywords
Easily capture bookmarks, articles, tweets, notes, and other web content into a unified knowledge hub
Acts as a 'second brain' that helps you connect and rediscover previously saved information
Offers integrations and a browser extension for frictionless capture of content
Useful for chatting with your own saved knowledge base via an AI interface

Recommended for

Researchers and students who collect and reference large amounts of information
Content creators and writers who need to organize inspiration and source material
Knowledge workers wanting a personal 'second brain' for productivity
Developers building AI apps that need a memory or knowledge layer
Anyone who bookmarks heavily and struggles to find saved content later

Analysis of Graphiti

Overall verdict

Graphiti is a well-regarded open-source framework for building real-time, temporally-aware knowledge graphs, particularly useful for AI agents and applications that need persistent, evolving memory. It's actively maintained by Zep and has gained solid traction in the LLM and agent development community.

Why this product is good

Purpose-built for real-time knowledge graphs that update incrementally without full recomputation
Temporal awareness lets it track how facts and relationships change over time
Designed specifically for AI agent memory, enabling more context-aware and persistent applications
Integrates with LLMs and supports hybrid retrieval (semantic, keyword, and graph-based search)
Open-source with active development and backing from Zep, plus growing community adoption
Scalable architecture suitable for production use cases involving dynamic data

Recommended for

Developers building AI agents that need long-term, evolving memory
Teams creating LLM-powered applications requiring context-aware retrieval
Projects needing temporally-aware knowledge graphs that track changes over time
Use cases involving dynamic, frequently-updated data rather than static datasets
Engineers exploring alternatives to traditional RAG for more structured, relational context

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Graphiti videos

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What is Graphiti Temporal Knowledge Graph?

Category Popularity

0-100% (relative to Supermemory and Graphiti)

Graphiti

84 84%

16% 16

Developer Tools

77 77%

Developer Tools

23% 23

Productivity

100 100%

Productivity

0% 0

AI Tools

67 67%

AI Tools

33% 33

User comments

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Social recommendations and mentions

Based on our record, Graphiti should be more popular than Supermemory. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Supermemory mentions (3)

Building an autonomous Slack agent with OpenCode
Memory. I use Supermemory for this. Before, Pipa loaded context files and knew to update them. A memory tool adds teammate-like recall: goals, preferences, latest business state, and small details that should carry across runs. Good memory tools also know how to supersede and delete memories, which matters once the agent has more autonomy. - Source: dev.to / about 1 month ago
Build a Real-Time Voice RAG Agent for Your Documentation
We wire everything up with Vision Agents as the voice agent framework, Stream for WebRTC audio and video, OpenAI Realtime for speech in and speech out, Anam so the agent shows up as a face on the video, and Supermemory so answers come from search over your uploaded documents instead of guesswork. The code stays small and most of the behavior lives in one registered function that asks the memory store for relevant... - Source: dev.to / 3 months ago
Ask HN: What are you working on (August 2024)?
My friends and I are working on https://supermemory.ai, an AI second brain to help you remember content from saved webpages and notes. - Source: Hacker News / almost 2 years ago

Graphiti mentions (9)

Your AI Agent Forgets Everything After Every Session. Graphiti Fixes That.
Graphiti is an open-source framework by Zep for building and querying temporal context graphs for AI agents. It's the engine behind Zep's managed memory platform, but it's fully usable standalone. - Source: dev.to / about 1 month ago
I Tested 33 AI Memory Engines — Here's What Actually Works
Graphiti by Zep is the temporal knowledge graph. Its core insight: knowing the current state isn't enough. You need to know when things changed and what was true before. - Source: dev.to / 2 months ago
I Built Two Ollama Tools I Don't Actually Need Yet
Several services share the same Ollama instance on a dedicated host that homelab-agent is provisioning: LibreChat for interactive chat, a SearXNG MCP server for ML-reranked search, and three background embedding jobs — graphiti, jobsearch-mcp, and memsearch-watch. - Source: dev.to / 3 months ago
I Benchmarked Graphiti vs Mem0: The Hidden Cost of Context Blindness in AI Memory
It started with a 35,000-token "Master Prompt" that she maintained manually in Notion. Every time something changed in her life, she updated it by hand. That obviously didn't scale. So I moved to Graphiti, a knowledge graph framework that extracts entities and relationships from conversations automatically. - Source: dev.to / 4 months ago
Show HN: A file-based agent memory framework that works like skill
- *[Zep](https://github.com/getzep/graphiti)* uses graphs, which handle structure well but add complexity and maintenance overhead. - Source: Hacker News / 7 months ago