KMeans vs DBSCAN

Interactive clustering comparison — pick a dataset, tweak parameters, hit Run Analysis.

① Choose a Dataset
② Tweak Parameters & Run
Dataset Size:
⚡ Larger = slower DBSCAN (great for benchmarks!)
KMeans Parameters
DBSCAN Parameters
KMeans centroid-based
Select a dataset and click Run Analysis
DBSCAN density-based
Select a dataset and click Run Analysis
📝 Algorithm Source Code Click to expand

📖 Further Reading

Articles from the Observability is Engineering series that go deeper on topics covered here.

🔬
Clustering Algorithms in Observability
Observability is Engineering · Medium
KMeans vs DBSCAN across four real-world observability shapes — with benchmark data drawn directly from this interactive tool.
📐
How Can I Find Customers I Should Focus On? Elbow to the Rescue
Observability is Engineering · Medium
The elbow method explained — a practical technique for picking the right K in KMeans without guessing.
🔗
Correlating System Log Lines with Grouping and K-Means in C#
Observability is Engineering · Medium
A real-world implementation of KMeans for log correlation — from raw log lines to actionable cluster insights.