We’re excited to share one of our biggest releases to date, with a little (or a lot!) for everyone. We’ll be sharing guides in the coming weeks on individual features, and some of our favorites already include:
- Graph Dashboarding: Interactive dashboards enable graph for much more of your team. The current release integrates our open source project graph-app-kit. You can now quickly edit Streamlit dashboards from the notebook UI and publish them either publicly or only to other staff/admin users. Our enterprise design partners already love this feature.
- PyGraphistry[AI]: AutoML for graph — automatically prepare any table or graph for graph AI with the new automatic feature encoding, even big text columns, and then send through our automatic graph AI methods. The UMAP support is especially amazing and one of our top techniques by our own graph AI professional services team. Popular classic graph algorithms are also now just a 1-liner away via the streamlined bindings for igraph (cpu) and cugraph (gpu).
- Chain, hop, and highlight: As growing the compute-tier graph capabilities, we are starting to enable a subset of the cypher pattern-matching language on dataframes and visuals
- Microsoft PowerBI: Many of our enterprise users have their data going through PowerBI and their analysts are quite comfortable using it — we are in active beta on enabling teams to bring their graph journey to their favorite SQL environment.
- Kubernetes: A lot is happening here for our bigger users with our new open source Helm charts for Graphistry
- Organizations: We’ll be announcing more here as Organizations go public on Hub as well
Learn more in our public release notes.