Explore 100X Bigger Graphs with the Graphistry 100X Initiative

For day 2 of our July announcements heading into Black Hat 2026 & AI4: We’re enabling Graphistry users to visually analyze 100X bigger graphs with the Graphistry 100X Initiative.

The video above revisits visually investigating 2 weeks of real network and device alerts in a large organization, scaling what was possible when Graphistry won the US Cyber Command 2024 AI alert competition (recording).

The Graphistry 100X Initiative is targeting across-the-board 100X scale increases over the next year for both bigger graphs and more concurrent users. This summer’s 10X rendering-engine updates extend Graphistry’s lead as one of the most scalable interactive graph visualization engines, now supporting 20M+ edges. Our earlier related announcement this week also shared that GFQL is now the fastest open-source Cypher property graph engine across many popular benchmarks and without requiring the pains of a database.

Graphistry remains the only browser-based graph visualization engine reliably handling full real-time interactive layout on large graphs – it solves common gaps like requiring static precomputed layouts. For example, GPU-accelerated desktop tools like Gephi and Cytoscape can support large graphs, and while not as big as Graphistry, the bigger practical issue is requiring a local install for those scales. GPU systems, including Cosmos, often require heavier hardware than many users will have, which Graphistry is designed to handle much better. More portable browser libraries like sigma.js, vis.js, and D3 do not run at these sizes. Once graph properties must also load alongside the nodes and edges, which is key to interactive analysis, Graphistry’s design matters even more.

The summer upgrades expands where Graphistry is the right tool:

We now recommend to choose Graphistry when:

• Your graph is too big for regular browser libraries – typically 100k+ edges – and you don’t want desktop installs.
• You need to explore — interactive layout, filtering, drill-down — not render a static figure.
• You want to use AI features to more easily understand and manipulate the graph.
• Your data is already in Python, dataframes, Parquet, a database, or a lakehouse.
• You’re doing security, fraud, social, IT, supply-chain, and other investigations where the graph represents many richly attributed events and entities.
• You want to share live views by URL with people who don’t have the tooling installed.
• You are building notebooks, dashboards, and web apps, including via a code agent
• You want to start with a free solution and using open source libraries

When something else fits better: For a small diagram or a graph with hundreds of nodes and little visual component integration, libraries such as D3 or sigma.js can be simple. Graphistry also works alongside databases and query engines: use GFQL to quickly turn regular tabular data into graphs without adding a separate graph database.

Next steps

The easiest thing to do is:

1. Get a free account and api key at hub.graphistry.com
2. Quickly start with the built-in file uploader or a client API:

• pip install graphistry
• npm i @graphistry/node-api
• npm i @graphistry/client-api
• REST: https://hub.graphistry.com/docs/api/ 
• Skills files for coding agents: https://github.com/graphistry/graphistry-skills 

For those who will soon be in Las Vegas for the week of Black Hat, AI4, BSides, and DefCon, we want to meet you! Likewise, reach out to say hello as the Graphistry and Louie.ai teams head to LA, SF (SANS), Park City, Canberra (BSides), Austin (LASCON), Miami, and DC.

For the other announcements, check out yesterday’s on Louie.ai topping the latest CyBT-CTF AI investigation leaderboard winner with +19% over OpenAI’s Codex agent, and how GFQL is beating most graph databases across major benchmarks.