totogo/awesome-knowledge-graph

What it solves

This project addresses the challenge of navigating the fragmented landscape of knowledge graph technology. It serves as a centralized hub to help developers, researchers, and data engineers find the right tools, datasets, and learning resources without having to search across disparate sources.

How it works

It is a curated, community-maintained directory of resources organized into logical categories. The list covers the entire lifecycle of knowledge graphs, including infrastructure (databases and triple stores), construction tools, visualization engines, query languages, and existing public datasets. It also provides links to educational materials, books, and conferences to support ongoing learning.

Who it’s for

This repository is for anyone working with connected data, ranging from beginners looking for their first tutorial to enterprise architects evaluating graph database vendors or researchers seeking large-scale datasets for machine learning and semantic analysis.

Highlights

• Infrastructure: A comprehensive list of graph databases, including multi-model, distributed, and in-memory options.
• Visualization: Tools and libraries for rendering complex graph data, from simple web-based toolkits to GPU-accelerated analytics engines.
• Datasets: Links to major public knowledge graphs like Wikidata, DBpedia, and domain-specific resources in medicine and academia.
• Learning: Curated documentation, books, and courses to help users transition from traditional SQL to graph query languages like Gremlin and Cypher.