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Raphtory is a powerful analytics engine for large-scale graph analysis. It lets you run complex queries on your data, no matter where it's stored or what format it's in. But that's not all - Raphtory's real superpower is its ability to track and explore the history of a complex system, from "time traveling" through data to executing advanced analysis like taint tracking, temporal reachability, and mining temporal motifs.

Raphtory is easy to use: just run a single pip install raphtory command and embed it with your existing Python/Pandas pipeline for input and output.

Raphtory is expressive: It's designed to represent all types of graph queries and has a well-developed API for exploring your data across its history.

Raphtory is lightning-fast and scales effortlessly: Our core is built upon rust. Raphtory can be run on a laptop or a distributed cluster for terabyte-scale graphs.

If you want to checkout the main Raphtory repo can be found here. It is managed by Pometry, the company developing Raphtory.

This organisation is for our experiments/alpha versions of Raphtory, such as the Docbrown rust rewrite, which was folded into Raphtory for the 0.3.0 release. You are more than welcome to dig into the projects below, and if you have any questions hit up the team on our Slack.