Prometheus vs Wavefront by VMware

Struggling to choose between Prometheus and Wavefront by VMware? Both products offer unique advantages, making it a tough decision.

Prometheus is a Ai Tools & Services solution with tags like monitoring, alerting, metrics.

It boasts features such as 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 pros including 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.

On the other hand, Wavefront by VMware is a Ai Tools & Services product tagged with metrics, monitoring, analytics, cloud, visibility.

Its standout features include Real-time metrics monitoring, Automatic anomaly detection, Integration with various data sources, Visualization and dashboards, Alerting and notifications, Cloud environment support, and it shines with pros like Scalable and handles high data volumes, Fast anomaly detection, Pre-built integrations for many data sources, Powerful visualization and dashboarding capabilities, Flexible pricing model.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Prometheus

Prometheus

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.

Categories:
monitoring alerting metrics

Prometheus Features

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

Pricing

  • Open Source

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


Wavefront by VMware

Wavefront by VMware

Wavefront by VMware is a SaaS-based metrics monitoring and analytics platform that provides real-time granular visibility into cloud environments. It specializes in handling high data volumes from various sources and detecting anomalies.

Categories:
metrics monitoring analytics cloud visibility

Wavefront by VMware Features

  1. Real-time metrics monitoring
  2. Automatic anomaly detection
  3. Integration with various data sources
  4. Visualization and dashboards
  5. Alerting and notifications
  6. Cloud environment support

Pricing

  • Subscription-Based

Pros

Scalable and handles high data volumes

Fast anomaly detection

Pre-built integrations for many data sources

Powerful visualization and dashboarding capabilities

Flexible pricing model

Cons

Can be complex to set up and configure initially

Limited custom alerting options

Less flexible than open source alternatives

Requires vendor lock-in