Open Web Analytics vs Prometheus

Struggling to choose between Open Web Analytics and Prometheus? Both products offer unique advantages, making it a tough decision.

Open Web Analytics is a Business & Commerce solution with tags like open-source, web-analytics, traffic-tracking, usage-analytics.

It boasts features such as Open source web analytics software, Easy to install and configure, Tracks website visitors and traffic sources, Provides reports on visits, page views, referrers, search keywords, Customizable dashboards and reporting, Event and goal tracking, Support for A/B testing, API for data export and integration, Works with MySQL, PostgreSQL and MS SQL databases and pros including Free and open source, Easy to set up and use, Provides core web analytics functionality, Customizable and extensible, Self-hosted - you control your data, Active development community.

On the other hand, Prometheus is a Ai Tools & Services product tagged with monitoring, alerting, metrics.

Its standout features include Multi-dimensional data model with time series data identified by metric name and key/value pairs, PromQL, a flexible query language to leverage this dimensionality, No reliance on distributed storage; single server nodes are autonomous, Time series collection happens via a pull model over HTTP, Pushing time series is supported via an intermediary gateway, Targets are discovered via service discovery or static configuration, Multiple modes of graphing and dashboarding support, and it shines with pros like Highly dimensional model allows flexible and efficient queries, PromQL supports aggregation and recording rules for pre-calculation, Built-in alerting and notification routing, Highly available with simple operational model, Native support for Kubernetes, Strong ecosystem integration.

Feature	Open Web Analytics	Prometheus
Overall Score	N/A	1
Primary Category	Business & Commerce	Ai Tools & Services

Product Overview

Open Web Analytics

Description: Open Web Analytics (OWA) is an open source web analytics software that allows you to track and analyze traffic on your website. It is designed to be easy to install and use, while providing detailed analytics reports.

Prometheus

Description: Prometheus is an open-source systems monitoring and alerting toolkit. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if certain conditions are met.

Key Features Comparison

Open Web Analytics Features

• Open source web analytics software
• Easy to install and configure
• Tracks website visitors and traffic sources
• Provides reports on visits, page views, referrers, search keywords
• Customizable dashboards and reporting
• Event and goal tracking
• Support for A/B testing
• API for data export and integration
• Works with MySQL, PostgreSQL and MS SQL databases

Prometheus Features

• Multi-dimensional data model with time series data identified by metric name and key/value pairs
• PromQL, a flexible query language to leverage this dimensionality
• No reliance on distributed storage; single server nodes are autonomous
• Time series collection happens via a pull model over HTTP
• Pushing time series is supported via an intermediary gateway
• Targets are discovered via service discovery or static configuration
• Multiple modes of graphing and dashboarding support

Pros & Cons Analysis

Open Web Analytics

Pros

• Free and open source
• Easy to set up and use
• Provides core web analytics functionality
• Customizable and extensible
• Self-hosted - you control your data
• Active development community

Cons

• Less features than commercial solutions
• Requires technical expertise to install and manage
• Limited support options
• Not as user friendly as some tools
• Potential security risks if not updated regularly

Prometheus

Pros

• Highly dimensional model allows flexible and efficient queries
• PromQL supports aggregation and recording rules for pre-calculation
• Built-in alerting and notification routing
• Highly available with simple operational model
• Native support for Kubernetes
• Strong ecosystem integration

Cons

• Pull-based model can miss short-lived spikes between scrapes
• No automatic removal of stale metrics (extra storage usage)
• Limited tooling for stats analysis, forecasting, anomaly detection
• No built-in federation for massive scale
• Steep learning curve for PromQL and architecture

Pricing Comparison

Open Web Analytics

• Open Source

Prometheus

• Open Source