I built a Zero-Allocation C# Knowledge Graph (because JVM graphs are too bloated)
Ian Cowley has developed Glacier.Graph, a zero-dependency C# Knowledge Graph aimed at overcoming the limitations of traditional Java-based graph databases. This new graph engine utilizes a Forward Star representation to achieve high performance without the overhead of object-oriented programming. It allows for rapid traversal and persistence of large graphs, significantly improving efficiency for AI applications.
- ▪Glacier.Graph can persist 230,000 edges to disk in just 30 milliseconds.
- ▪The engine uses flat, primitive integer arrays instead of objects to avoid memory allocation issues.
- ▪Traversing a graph of 150,000 nodes took only 5.3 milliseconds to find a path.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3928889) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Ian Cowley Posted on May 18 I built a Zero-Allocation C# Knowledge Graph (because JVM graphs are too bloated) #ai #dotnet #performance #database If you are building AI agents, you eventually hit the "Memory Wall". Your agent doesn't just need semantic text chunks (Vector Search) or structured tables (SQL). It often needs to trace relationships. For example: Find all suppliers connected to this failing part, or Find the common connection between User_A and User_B.
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