Raphtory is an open-source platform for distributed real-time temporal graph analytics, allowing you to load and process large dynamic datasets across time.
If you would like a brief summary of what it's used for before fully diving in please check out our Raphtory Overview! Alternatively you can watch our most recent talks on Raphtory at AIUK, The Knowledge Graph Conference and NetSciX.
Alongside our talks we regularly post blogs about releases, new features and interesting uses cases, all of which are searchable above.
If you like what you see you should
Give Raphtory a go! We have a fantastic tutorial showing you
how to get everything setup, get your first Raphtory instance running and submit your first temporal graph
algorithms.
Come and chat to the community on Slack! Feel free to join the #raphtory-development and #askaway channels to discuss current issues or ask any questions.
Come and say hello to us on Twitter. Any and all feedback is welcomed!
If you want to contribute to the project you can
Checkout our Bounty Board where we keep track of all the functionality and algorithms we want to implement. There are many labeled as low hanging fruit (
) just waiting for a newbie to tackle. For bugs and miscellaneous suggestions, you can checkout our Git Issues.
) just waiting for a newbie to tackle. For bugs and miscellaneous suggestions, you can checkout our Git Issues.
Once you know what you want to work on, head over to the Github repo and give us a clone. The project is straight forward to get running, but everyone on slack is always there to give a hand.
If you want to run Raphtory in production you should
Drop a line to the team at Pometry who are developing enterprise Raphtory plugins and providing seemless deployment for terabyte scala graphs.