VictoriaMetrics

open_source

VictoriaMetrics is a high-performance, open-source time series database and monitoring solution. Prometheus-compatible, cost-efficient, and built for scale.

Data & Analytics

AI Models & Infrastructure

Analytics Databases

About

VictoriaMetrics is a fast, cost-efficient, and scalable observability stack built by engineers, for engineers. At its core is a high-performance time series database that acts as a drop-in replacement for Prometheus, supporting PromQL and MetricsQL query languages. The platform covers the full observability stack: VictoriaMetrics for metrics, VictoriaLogs for mission-critical log management, and VictoriaTraces for distributed tracing data storage and querying. Designed for simplicity and reliability, VictoriaMetrics can be deployed on-premise, in Kubernetes clusters, or consumed as a fully managed cloud service (VictoriaMetrics Cloud). Its Enterprise tier adds anomaly detection powered by AI, expert support, advanced downsampling, and long-term retention capabilities. Key strengths include dramatically reduced storage and compute costs compared to alternatives like Grafana/Mimir or InfluxDB—with users reporting up to 10x lower AWS bills—while handling billions of time series with ease. With over 16,000 GitHub stars, 1B+ Docker pulls, and adoption at organizations ranging from startups to CERN and IHI Terrasun, VictoriaMetrics is a proven choice for teams needing production-grade monitoring without operational complexity.

Key Features

High-Performance Time Series Database: Handles billions of time series with exceptional speed and efficiency, outperforming Prometheus and InfluxDB in large-scale deployments.
Prometheus & OpenTelemetry Compatibility: Acts as a drop-in replacement for Prometheus with full PromQL support, enabling seamless migration without rewriting queries or code.
Full Observability Stack: Covers metrics (VictoriaMetrics), logs (VictoriaLogs), and distributed traces (VictoriaTraces) in a single unified platform.
Flexible Deployment Options: Deploy on-premise, in Kubernetes, or use VictoriaMetrics Cloud for a fully managed, out-of-the-box observability experience.
AI-Powered Anomaly Detection: Enterprise tier includes machine learning-based anomaly detection to proactively identify unusual patterns in your metrics.

Use Cases

Infrastructure monitoring for large-scale Kubernetes and cloud environments requiring efficient long-term metrics retention
Replacing Prometheus or InfluxDB to reduce storage and compute costs while maintaining full query compatibility
Industrial IoT data collection and analysis, such as processing millions of sensor metrics per second from solar panels or manufacturing equipment
Scientific and research institution monitoring where high-volume time series data must be stored reliably over long periods
SaaS and enterprise application performance monitoring with AI-powered anomaly detection to proactively catch incidents

Pros

Dramatic Cost Savings: Users report up to 10x lower infrastructure costs compared to alternatives like Grafana Cloud (Mimir) or InfluxDB due to superior data compression and efficiency.
Easy Migration from Prometheus: Full Prometheus compatibility means teams can switch in as little as 20 minutes without changing existing queries, dashboards, or instrumentation code.
Scales to Massive Workloads: Proven at scale by organizations handling millions of metrics per second, including scientific institutions and large tech companies.
Open Source with Enterprise Support: The core product is free and open source with an active community, while enterprise and cloud tiers provide expert support for demanding use cases.

Cons

Learning Curve for MetricsQL: VictoriaMetrics introduces its own MetricsQL query language with extensions beyond PromQL, which requires additional learning for teams already familiar with Prometheus.
Advanced Features Behind Enterprise Paywall: Key capabilities like anomaly detection, advanced downsampling, and long-term retention are locked behind the paid Enterprise tier.
Less Ecosystem Integration Than Grafana Stack: While highly compatible, VictoriaMetrics has a smaller ecosystem of native integrations and community plugins compared to the broader Grafana/Prometheus ecosystem.

Frequently Asked Questions

Yes. VictoriaMetrics is a drop-in replacement for Prometheus. It supports the Prometheus data model, PromQL queries, and Prometheus-compatible remote write/read APIs, so you can migrate without changing your existing queries or instrumentation.

The open source version is a fully functional, high-performance time series database free to use. The Enterprise tier adds AI-powered anomaly detection, advanced downsampling, long-term retention policies, multi-tenancy, and dedicated expert support.

Yes. VictoriaMetrics provides a Kubernetes Operator and Helm charts for easy deployment in Kubernetes clusters, making it straightforward to run as part of a cloud-native observability stack.

Yes. VictoriaMetrics offers a full observability stack: VictoriaMetrics for time series metrics, VictoriaLogs for log management, and VictoriaTraces (newer) for distributed tracing data storage and querying.

VictoriaMetrics Cloud is a fully managed, out-of-the-box observability service hosted by VictoriaMetrics. It removes the operational burden of self-hosting while delivering the same performance and cost-efficiency benefits of the core platform.