Visualize graphs at scale
Sigma.js (sigmajs.org) scores 65 out of 100 on Brand Analyzer, placing it in the Developing tier among Technology brands, SaaS brands, Other brands, in the 13th percentile of 34613 Technology brands.
Sigma.js is a JavaScript library designed for visualizing and interacting with graphs containing thousands of nodes and edges directly in the browser. It focuses on high-performance rendering of large-scale network graphs and works alongside graphology, a companion library for graph data modeling and algorithms. Sigma.js is open-source and targets web developers, data scientists, and software engineers who need to display complex network structures in web-based applications.
| Brand Name | Sigma.js |
|---|---|
| Domain | sigmajs.org |
| Industry | Technology, SaaS |
| Main Competitors | D3.js (73/100), Cytoscape.js, vis.js (63/100), Gephi (84/100), G6 (AntV), Neo4j Bloom (93/100) |
Moz Domain Authority 49/100 vs category average 40 / leader 100 - a strong backlink profile, so AI systems frequently encounter mentions of the brand.
Ranked #695,080 on the Tranco list of most-visited sites - modest traffic makes the brand easy for AI models to overlook.
No Wikipedia presence was found - a major gap, since Wikipedia is among the most heavily weighted sources in AI training data.
The homepage meta description reads "a JavaScript library aimed at visualizing graphs of thousands of nodes and edges" (Meta description: 13 words (ideal length). No OG description (falling back to meta)) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: No structured data or Open Graph tags detected. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: No robots.txt found (default: all bots allowed, but explicit file preferred) - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Detected tech stack: Angular.
Social footprint: verified profiles on GitHub, X (Twitter), Instagram; no detected presence on LinkedIn, Facebook, YouTube - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
Live results from asking a general-purpose AI assistant about the brand, checked September 2026.
When asked "What is Sigma.js?", Claude could identify the brand as of September 2026. Sigma.js is an open-source JavaScript library for rendering and interacting with graph and network visualizations directly in web browsers, using WebGL/canvas for performance with large datasets. It's commonly used alongside graph analysis libraries like graphology to build inter Best known for Fast, browser-based rendering of large network graphs using WebGL.
When asked "Best brands similar to Sigma.js?", Claude would recommend Sigma.js as of September 2026. It's a well-known, widely used tool among developers building graph visualization features, especially for performance with large networks.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
Sigma.js's main competitors in Technology: D3.js (73/100), vis.js (63/100), Gephi (84/100), Neo4j Bloom (93/100).
Sources: Brand Analyzer scan
Sigma.js is a JavaScript library aimed at visualizing graphs of thousands of nodes and edges. It is designed for rendering and interacting with large-scale network graphs directly in a web browser, and it is described as a graph drawing library in knowledge-graph terms.
Sources: Sigma.js official site
Sigma.js has limited AI-search visibility, scoring 30/100 on Brand Analyzer's AI visibility composite (visibility 18, trust 26, recommendation 55). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
Sources: Sigma.js official site
Sigma.js offers an open-source JavaScript library for rendering and visualizing network graphs in the browser. It provides tools for displaying and interacting with large graphs of thousands of nodes and edges, and is designed to work alongside graphology, a companion library for graph data structures and algorithms.
Sources: Sigma.js official site
Sigma.js renders and enables interaction with large-scale network graphs in the browser. It handles the visualization layer, allowing developers to display thousands of nodes and edges efficiently, while working in symbiosis with graphology, a separate library that manages graph data modeling and algorithms.
Sources: Sigma.js official site
Sigma.js scores 55/100 on Brand Analyzer's AI recommendation signal, indicating it is reasonably likely to be surfaced when AI assistants like ChatGPT suggest Technology options. Recommendation depends on crawlability, structured data, and category authority.
Sources: Sigma.js official site
Sigma.js can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
Sources: Sigma.js official site
Sigma.js is used by web developers, data scientists, and software engineers who need to visualize and interact with complex network graphs in browser-based applications.
Sources: Sigma.js official site
Sigma.js is known for enabling high-performance visualization of large network graphs-specifically graphs containing thousands of nodes and edges-within web browsers using JavaScript. It is recognized as an open-source solution that pairs with the graphology library for graph data management.
Sources: Sigma.js official site
Sigma.js scores 30/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
Sigma.js has a weak AI-visibility profile at 30/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is recommendation likelihood (55/100) and its weakest is visibility (18/100). It benefits from a Wikidata knowledge-graph entry, a global traffic rank of #695,080 (Tranco) and a Moz Domain Authority of 49/100. The main gaps holding it back: no clear Wikipedia entity to anchor it in LLM training data, thin schema.org structured data and no llms.txt to steer AI to its best pages. In a live check, Claude could already identify Sigma.js from memory (September 2026) - a sign these signals are paying off.
The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark.
Ranked closest to Sigma.js: Siftt.AI (65/100), Shihuo (65/100), Sigma Software, Inc. (65/100), Signifi Solutions (65/100).
A step up - brands to learn from: Zocket (71/100), Zhangyue (71/100).
Category leader: Hostinger (97/100).
Brand Analyzer is built by DataEase AI. Track your brand in ChatGPT, Gemini and Perplexity.