Cacti vs Prometheus: What are the differences?

Introduction

Cacti and Prometheus are both monitoring solutions widely used in the IT industry. Although they serve a similar purpose, there are several key differences between the two.

1. Data Storage: One of the primary differences between Cacti and Prometheus lies in their approach to data storage. Cacti relies on RRDtool, a round-robin database, to store and graph data over time. On the other hand, Prometheus uses a custom time-series database specifically designed for monitoring purposes, allowing for more efficient storage and retrieval of data.

2. Data Collection: Cacti primarily relies on SNMP (Simple Network Management Protocol) for data collection. It polls devices at regular intervals to gather metrics. In contrast, Prometheus follows a pull-based model where it scrapes metrics from the monitored targets using HTTP. This approach provides more flexibility in terms of target discovery and monitoring various types of applications.

3. Metric Filtering and Aggregation: Cacti offers limited options for metric filtering and aggregation. It mainly focuses on presenting the raw data collected. In contrast, Prometheus provides a powerful querying language called PromQL, allowing users to filter, aggregate, and manipulate metrics based on specific conditions. This capability enables complex analysis and alerting mechanisms.

4. Alerting: Cacti lacks built-in alerting capabilities. Users need to rely on external plugins or scripts to set up alerting rules. Prometheus, on the other hand, comes with a robust alerting system. It allows users to define alerting rules based on metric thresholds or specific conditions and sends notifications when these rules are violated.

5. Ecosystem and Integration: Cacti offers a wide range of plugins and extensions to extend its functionality. It integrates well with various third-party tools and services. Prometheus, on the other hand, has a vast ecosystem with numerous exporters, integrations, and visualization tools developed by the community. Its native integration with Kubernetes and extensive exporter library makes it a popular choice in containerized environments.

6. Scalability and High Availability: Cacti's architecture is generally suitable for small and medium-scale deployments. It can struggle to handle large amounts of data or high-frequency monitoring. In contrast, Prometheus is designed with scalability and high availability in mind. It supports federation and horizontal scaling, allowing users to handle massive amounts of data and ensure reliable monitoring even in distributed environments.

In summary, Cacti relies on RRDtool for data storage, uses SNMP for data collection, lacks advanced filtering, aggregation, and native alerting capabilities, offers a rich ecosystem of plugins but may have limitations in scalability. Prometheus, on the other hand, uses a custom time-series database, employs a pull-based data collection model, offers powerful metric filtering and aggregation features with PromQL, has built-in alerting capabilities, a robust ecosystem, and is designed for scalability and high availability.