Graphology¶

Graphology is a specification and reference implementation for graph data structures in JavaScript.

Overview¶

Property	Value
Type	In-Memory Graph Library
Language	JavaScript/TypeScript
License	MIT
Architecture	Pure JavaScript
API	Custom JS API
Website	graphology.github.io
GitHub	github.com/graphology/graphology

Performance Summary¶

### Overall Score: **58.2/100** - 5th Place | Metric | Score | Rank | |--------|-------|------| | Ingestion | 4th | 78K nodes/s | | Traversal | 4th | 3.4ms avg | | PageRank | 5th | 6.2s (10 iter) | | Memory | 4th | 125 MB |

Key Characteristics¶

Strengths¶

Pure JavaScript - No native compilation needed
Browser Support - Runs in any modern browser
TypeScript Support - Full type definitions
Modular - Use only what you need
Ecosystem - Many extensions available

Weaknesses¶

Slowest PageRank - 440% slower than CongraphDB
High Memory - V8 object overhead
Single Threaded - No parallel processing
No Persistence - In-memory only (by default)

Performance Analysis¶

Ingestion Performance¶

Scale	Nodes/s	vs CongraphDB
Small (10K)	78,000	-38%
Medium (100K)	72,000	-39%
Large (1M)	68,000	-38%

Why slower: - JavaScript object allocation overhead - V8 hidden class transitions - No native code optimization - Garbage collection pauses

Traversal Performance¶

Hops	Small	Medium	Large
1-hop	0.15ms	0.18ms	0.22ms
2-hop	0.40ms	0.48ms	0.58ms
3-hop	1.10ms	1.25ms	1.50ms
4-hop	3.20ms	3.80ms	4.50ms
5-hop	8.50ms	10.20ms	12.80ms

Why competitive: - Direct object property access - No network overhead - In-memory adjacency lists - V8 JIT optimization

Memory Usage¶

Scale	Peak Memory	vs CongraphDB
Small (10K)	125 MB	+178%
Medium (100K)	980 MB	+155%
Large (1M)	8,500 MB	+162%

Why high memory: - JavaScript object headers (~32 bytes per object) - V8 hidden classes - Property storage overhead - No memory compaction

When Graphology Makes Sense¶

Choose Graphology For¶

✅ Browser Applications - Only option for client-side graphs
✅ Pure JS Stack - No native compilation
✅ Temporary Graphs - In-memory processing only
✅ Visualization - Works well with sigma.js

Avoid Graphology For¶

❌ Performance Critical - 38% slower than CongraphDB
❌ Large Datasets - High memory usage
❌ Server-Side - CongraphDB is better for Node.js
❌ Persistent Storage - No built-in persistence

Code Example¶

import Graph from 'graphology';

// Create graph
const graph = new Graph();

// Add nodes
papers.forEach(paper => {
  graph.addNode(paper.id, {
    title: paper.title,
    year: paper.year,
    venue: paper.venue
  });
});

// Add edges
citations.forEach(cit => {
  graph.addEdge(cit.source, cit.target, {
    label: 'CITES',
    since: cit.year
  });
});

// Traversal
const neighbors = graph.neighbors(paperId); // 1-hop
const twoHop = new Set();
graph.forEachNeighbor(paperId, (node) => {
  graph.forEachNeighbor(node, (n) => twoHop.add(n));
});

// PageRank
import { pagerank } from 'graphology-metrics/centrality';
pagerank.assign(graph);

Ecosystem¶

Graphology has many companion libraries:

graphology-generators - Random graph generation
graphology-layout - Graph layout algorithms
graphology-metrics - Centrality, community detection
graphology-traversal - BFS, DFS, shortest paths
sigma.js - WebGL graph visualization

Resources¶

Summary¶

Graphology is the best choice for browser-based graph applications. For server-side Node.js applications, CongraphDB offers significantly better performance and lower memory usage.

Recommendation: Use Graphology for browser apps or when you need pure JavaScript; use CongraphDB for server-side Node.js applications.