Graphistry aligns with the way that you work, allowing you to bring next-generation visualization and analysis into your native environment. Easily add visual analytics to your existing dashboards to extend your existing tools and workflow. Data scientists can work with Graphistry directly from within their favorite data science notebooks, and developers can leverage the developer API to build a powerful visual front-end to any application. Work the way that you want, and we’ll bring the visualization.

Integrate with your favorite analyst notebook

Work Directly in Your Favorite Analyst Notebook

Call the PyGraphistry library directly from Jupyter, SageMaker, Databricks, Colab, and other popular Python data science environments. The Pandas-based API makes it easy to load data from CSVs, Spark, SQL, graph databases, and more. Directly load your own data tables and graphs. If you have custom analytics, you can annotate the data with their output, and explore the result with Graphistry.

Streamlit with Graphistry: Bring the power of visual graph intelligence to "The fast way to build and share data apps"!

Turn your graph data into a secure and interactive visual graph app in 15 minutes!

Graph-App-Kit is an open source project combining the graph intelligence powers of Graphistry with the dashboarding ease of Streamlit. It combines patterns the Graphistry team has reused across many graph projects as teams go from code-heavy Jupyter notebook experiments to deploying streamlined analyst tools. Whether building your first graph app, trying an idea, or wanting to check a reference, this project aims to simplify that process. Graph-App-Kit covers pieces like: Easy code editing and deployment, optional air-gapped self-hosting, a project structure ready for teams, built-in authentication, no need for custom JS/CSS, batteries-included data + library dependencies, and fast loading & visualization of large graphs.

Embed Graphistry or use it to build a powerful frontend for your new application

Powerful Development APIs

The REST API provides language-neutral support, and makes embedding easy with wrappers for Python, JavaScript, and React. Use it in a variety of ways:

  • Embed graph views into existing data-driven web applications, dashboards, and wikis.
  • Pioneer a new graph-capable application, where you can focus more on the data pipeline and theming than the underlying JavaScript & GPU graph code.
  • Create a suite of investigation templates for interacting with various data stores, and share them directly or enrich your current tools with quick launch links.