1. Data Model: Graphite uses a fixed data model with a hierarchical structure, where metrics are organized in a tree-like hierarchy. In contrast, Prometheus utilizes a dimensional data model, allowing for more flexible and efficient data querying based on key-value pairs.

2. Data Storage: Graphite typically stores data as flat files on disk, which can lead to scalability challenges for high-volume data. On the other hand, Prometheus stores data in a time-series database with more advanced storage mechanisms, enabling better performance and scalability.

3. Data Collection: StatsD is a simple protocol for collecting and aggregating custom application metrics, primarily focusing on UDP-based metric collection. In comparison, Prometheus comes with a built-in metrics collection mechanism, offering support for various service discovery options and comprehensive metric instrumentation.

4. Alerting Capabilities: While Graphite lacks built-in alerting capabilities, Prometheus has robust alerting functionalities integrated directly into the system, allowing users to define complex alerting rules based on metric queries and thresholds.

5. Data Visualization: Graphite provides basic data visualization capabilities through its integrated graphing features, but it may require additional tools for more advanced visualization. On the contrary, Prometheus offers built-in Grafana integration for sophisticated and customizable dashboard creation and visualization.

6. Community Support: Prometheus has a vibrant and active community that regularly contributes to the development and maintenance of the project, ensuring frequent updates, enhancements, and support. In contrast, Graphite's community support may be comparatively less extensive, impacting the availability of resources and expertise for troubleshooting and optimization.

In Summary, Graphite, Prometheus, and StatsD differ in their data models, storage mechanisms, data collection approaches, alerting capabilities, data visualization options, and community support.