VictoriaMetrics vs Prometheus

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

VictoriaMetrics is a Ai Tools & Services solution with tags like time-series, metrics, monitoring, alerting.

It boasts features such as High-performance time series database, Supports PromQL query language, Single-node and cluster modes, Data retention policies, Alerting and recording rules, Remote storage integrations, Grafana dashboard support and pros including High ingestion and query rates, Efficient storage format, Easy horizontal scaling, PromQL support provides query flexibility, Cost-effective compared to Prometheus.

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	VictoriaMetrics	Prometheus
Overall Score	N/A	1
Primary Category	Ai Tools & Services	Ai Tools & Services

Product Overview

VictoriaMetrics

Description: VictoriaMetrics is an open-source time series database optimized for high-cardinality data and high ingestion rates. It is a cost-effective alternative to Prometheus for monitoring and alerting.

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

VictoriaMetrics Features

• High-performance time series database
• Supports PromQL query language
• Single-node and cluster modes
• Data retention policies
• Alerting and recording rules
• Remote storage integrations
• Grafana dashboard support

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

VictoriaMetrics

Pros

• High ingestion and query rates
• Efficient storage format
• Easy horizontal scaling
• PromQL support provides query flexibility
• Cost-effective compared to Prometheus

Cons

• Less ecosystem support than Prometheus
• Limited dashboarding compared to Prometheus & Grafana
• No native visualization or dashboarding

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

VictoriaMetrics

• Open Source
• Free

Prometheus

• Open Source