Hy Memory (Official Website) is a production-grade dual-system cognitive memory engine and Python SDK (hy-memory) for self-evolving LLM agents, providing specialized memory pipelines across three task scenes: hierarchical long-term cognitive memory for Chat, two-layer fact and…
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#410 · +91 · 1d ·GitHub
MemoryBear is a next-generation AI memory system developed by RedBear AI. Its core breakthrough lies in moving beyond the limitations of traditional "static knowledge storage".
A super fast Graph Database uses GraphBLAS under the hood for its sparse adjacency matrix graph representation. Our goal is to provide the best Knowledge Graph for LLM (GraphRAG).
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory with small models for free
> Ingest your enterprise data, extract what matters, build a Context Graph and knowledge graph (KG), and run graph analytics and causal reasoning over all of it, with full decision provenance baked in. Explainable, traceable, and trustworthy by design.
A modern platform for visual, flexible, and extensible graph-based investigations. For cybersecurity analysts and investigators.
#1205 · +25 · 1d ·GitHub
Your company's data, connected into one ontology, on your own computer. A local-first data workspace built on HelixDB and DuckDB.
> Like DeepWiki, but deeper. DeepWiki helps you understand code. GitNexus lets you analyze it — a knowledge graph tracks every relationship, not just descriptions.
HydraDB is an object-store-native distributed graph database written in Rust. It combines durable graph storage on SlateDB with snapshot-consistent OpenCypher queries, GraphBLAS traversal, Neo4j-compatible Bolt connectivity, and an HTTPS query API.
> Note: You can also use pip if you prefer, but uv is recommended for better performance and more reliable dependency management.
MemOS is a Memory Operating System for LLMs and AI agents that unifies store / retrieve / manage for long-term memory, enabling context-aware and personalized interactions with KB, multi-modal, tool memory, and enterprise-grade optimizations built in.
\ Run it as a server, declared as code; hundreds of agents operate and enrich the graph on parallel isolated branches, and every change is reviewed and merged safely.
SurrealDB is a multi-model database built in Rust designed to unify multiple data models into a single engine.
An open source cybersecurity protocol for syncing decentralized graph data.
Dgraph is a horizontally scalable and distributed GraphQL database with a graph backend. It provides ACID transactions, consistent replication, and linearizable reads. It's built from the ground up to perform a rich set of queries.
is the world's leading Graph Database. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
A distributed, fast open-source graph database featuring horizontal scalability and high availability
#6161 · +1 · 1d ·GitHub
This repository is for BloodHound Legacy (version 4), which was last updated in 2023 and is no longer maintained. It will be archived in the near future.
Cayley is an open-source database for Linked Data. It is inspired by the graph database behind Google's Knowledge Graph (formerly Freebase)).
🥑 ArangoDB is a native multi-model database with flexible data models for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.
Learn: build an app with Gel • Website • Docs • Blog • Discord • Twitter
A bio-inspired cognitive memory engine — a new paradigm for Graph RAG.
Zilan (知澜) is an LLM-powered knowledge management and intelligent Q&A platform with a minimalist product experience that unifies RAG quick Q&A, ReAct agent reasoning, and auto-generated Wiki knowledge distillation.