Today's RAG & Vector Databases: Fastest-Growing Projects — May 04, 2026
Today's the RAG & Vector Databases space, we're seeing a surge in interest around tools that enable local-first knowledge base compilation and hybrid search capabilities. Repositories focused on Retrieval-Augmented Generation (RAG) frameworks for specific domains like Cyber Threat Intelligence (CTI) are also gaining traction. As developers increasingly seek to turn raw research into actionable insights, these tools are filling a critical gap.
Swarmclawai's SwarmVault leads the pack with a growth score of 18.81 and 323 stars. This local-first RAG knowledge base compiler allows users to transform raw research into a persistent markdown wiki, knowledge graph, and hybrid search that compounds over time, making it an attractive solution for researchers and developers seeking to streamline their workflow. With 100 commits in the past 30 days, SwarmVault's popularity is likely driven by its versatility and ease of use.
Rolandpg's Zettelforge boasts a growth score of 12.06 and 33 stars, indicating a promising trajectory for this Python-based agentic memory tool. By providing STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, and MCP server capabilities for Claude Code and LangChain agents, Zettelforge is poised to become a go-to solution for CTI professionals seeking to enhance their analytical workflows.
Nashsu's LLM Wiki has garnered an impressive 5,553 stars, with a growth score of 6.84. This cross-platform desktop application automatically turns documents into an organized, interlinked knowledge base, leveraging incremental building and maintenance capabilities to provide users with a persistent wiki from their sources. Its popularity can be attributed to its user-friendly interface and ability to revolutionize the way researchers interact with their data.
Ais1on's CTI-RAG framework has secured 214 stars and a growth score of 5.95, despite having no commits in the past 30 days. This Retrieval-Augmented Generation framework integrates knowledge graph and causal reasoning capabilities to provide security analysts with an intelligent threat intelligence analysis tool, making it an attractive solution for those seeking to enhance their CTI workflows.
Lastly, Yanhua1010's zero-to-ai-fullstack repository has gained a growth score of 4.14 and 150 stars. This Java backend engineer's public learning journey in AI full-stack development covers Python, FastAPI, RAG, pgvector, and Next.js, providing a valuable resource for developers seeking to upskill in the AI space. With 7 commits in the past 30 days, this repository is likely gaining traction due to its comprehensive coverage of key technologies.
Swarmclawai's SwarmVault leads the pack with a growth score of 18.81 and 323 stars. This local-first RAG knowledge base compiler allows users to transform raw research into a persistent markdown wiki, knowledge graph, and hybrid search that compounds over time, making it an attractive solution for researchers and developers seeking to streamline their workflow. With 100 commits in the past 30 days, SwarmVault's popularity is likely driven by its versatility and ease of use.
Rolandpg's Zettelforge boasts a growth score of 12.06 and 33 stars, indicating a promising trajectory for this Python-based agentic memory tool. By providing STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, and MCP server capabilities for Claude Code and LangChain agents, Zettelforge is poised to become a go-to solution for CTI professionals seeking to enhance their analytical workflows.
Nashsu's LLM Wiki has garnered an impressive 5,553 stars, with a growth score of 6.84. This cross-platform desktop application automatically turns documents into an organized, interlinked knowledge base, leveraging incremental building and maintenance capabilities to provide users with a persistent wiki from their sources. Its popularity can be attributed to its user-friendly interface and ability to revolutionize the way researchers interact with their data.
Ais1on's CTI-RAG framework has secured 214 stars and a growth score of 5.95, despite having no commits in the past 30 days. This Retrieval-Augmented Generation framework integrates knowledge graph and causal reasoning capabilities to provide security analysts with an intelligent threat intelligence analysis tool, making it an attractive solution for those seeking to enhance their CTI workflows.
Lastly, Yanhua1010's zero-to-ai-fullstack repository has gained a growth score of 4.14 and 150 stars. This Java backend engineer's public learning journey in AI full-stack development covers Python, FastAPI, RAG, pgvector, and Next.js, providing a valuable resource for developers seeking to upskill in the AI space. With 7 commits in the past 30 days, this repository is likely gaining traction due to its comprehensive coverage of key technologies.