Today's RAG & Vector Databases: Fastest-Growing Projects — April 30, 2026
Today's the RAG & Vector Databases space, we've seen a surge in innovative projects that combine AI-powered knowledge graphs and vector databases to enhance threat intelligence analysis, document organization, and conversational AI. The growth scores indicate a strong interest in these emerging technologies, with several repositories gaining significant traction on GitHub.
Rolandpg/zettelforge takes the top spot with a remarkable Growth Score of 13.50 and 33 stars. This Python-based repository provides an "agentic memory" for Cyber Threat Intelligence (CTI), featuring STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, and MCP server capabilities for Claude Code and LangChain agents. Its rapid growth can be attributed to its comprehensive feature set, making it a valuable resource for developers working on CTI projects.
Ais1on/CTI-RAG boasts an impressive 175 stars, despite a lower Growth Score of 5.79. This Retrieval-Augmented Generation (RAG) framework integrates knowledge graph and causal reasoning capabilities for Cyber Threat Intelligence analysis, providing security analysts with a powerful tool. Although it hasn't seen recent commits, its established user base and comprehensive feature set ensure its continued relevance in the space.
Yanhua1010/zero-to-ai-fullstack has garnered attention with a Growth Score of 4.73 and 151 stars. This Java backend engineer's public learning project showcases a full-stack AI implementation using Python, FastAPI, RAG, pgvector, and Next.js. Its growth can be attributed to the increasing interest in full-stack AI development and the value of publicly shared learning resources.
Nashsu/llm_wiki has achieved an impressive 4,961 stars, with a Growth Score of 4.30. This cross-platform desktop application transforms documents into an organized, interlinked knowledge base using incremental LLM wiki building and maintenance. Its massive user base and growth score indicate the strong demand for efficient document organization tools that leverage AI.
Zhanghang2017/AI-chat-rag rounds out our list with a Growth Score of 1.33 and 41 stars. This React+Node+LangChain-based project builds an intelligent conversational AI chat application using RAG. Although its growth score is lower, the repository's focus on conversational AI and RAG demonstrates the expanding interest in these areas.
Overall, Today's trends highlight the convergence of knowledge graphs, vector databases, and AI-powered tools for various applications, from threat intelligence analysis to document organization and conversational AI.
Rolandpg/zettelforge takes the top spot with a remarkable Growth Score of 13.50 and 33 stars. This Python-based repository provides an "agentic memory" for Cyber Threat Intelligence (CTI), featuring STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, and MCP server capabilities for Claude Code and LangChain agents. Its rapid growth can be attributed to its comprehensive feature set, making it a valuable resource for developers working on CTI projects.
Ais1on/CTI-RAG boasts an impressive 175 stars, despite a lower Growth Score of 5.79. This Retrieval-Augmented Generation (RAG) framework integrates knowledge graph and causal reasoning capabilities for Cyber Threat Intelligence analysis, providing security analysts with a powerful tool. Although it hasn't seen recent commits, its established user base and comprehensive feature set ensure its continued relevance in the space.
Yanhua1010/zero-to-ai-fullstack has garnered attention with a Growth Score of 4.73 and 151 stars. This Java backend engineer's public learning project showcases a full-stack AI implementation using Python, FastAPI, RAG, pgvector, and Next.js. Its growth can be attributed to the increasing interest in full-stack AI development and the value of publicly shared learning resources.
Nashsu/llm_wiki has achieved an impressive 4,961 stars, with a Growth Score of 4.30. This cross-platform desktop application transforms documents into an organized, interlinked knowledge base using incremental LLM wiki building and maintenance. Its massive user base and growth score indicate the strong demand for efficient document organization tools that leverage AI.
Zhanghang2017/AI-chat-rag rounds out our list with a Growth Score of 1.33 and 41 stars. This React+Node+LangChain-based project builds an intelligent conversational AI chat application using RAG. Although its growth score is lower, the repository's focus on conversational AI and RAG demonstrates the expanding interest in these areas.
Overall, Today's trends highlight the convergence of knowledge graphs, vector databases, and AI-powered tools for various applications, from threat intelligence analysis to document organization and conversational AI.