VictoriaMetrics: A Fast and Scalable Time-Series Database

Sébastien Puyet

Sébastien Puyet

— 2 min read
VictoriaMetrics: A Fast and Scalable Time-Series Database

When it comes to monitoring infrastructure, metrics collection and storage are critical. Traditional time-series databases like Prometheus or InfluxDB work well, but they can struggle with scale and long-term retention.

That’s where VictoriaMetrics comes in. It’s a fast, cost-effective, and scalable time-series database built specifically for monitoring and observability workloads.

What Is VictoriaMetrics?

VictoriaMetrics is an open-source time-series database and monitoring solution. It’s designed to store, query, and analyze huge volumes of metrics efficiently.

  • ⚡ High performance: Handles millions of metrics per second.
  • 💾 Efficient storage: Uses compression to reduce disk space.
  • 📈 Prometheus-compatible: Works as a drop-in replacement or long-term storage for Prometheus.
  • ☁️ Cloud-ready: Offers both single-node and cluster versions, plus a managed cloud service.

Why Choose VictoriaMetrics?

1. Scalability

VictoriaMetrics supports both single-node and clustered deployments, making it suitable for small setups or enterprise-scale infrastructures.

2. Cost Efficiency

Thanks to aggressive data compression, it reduces storage costs compared to Prometheus and InfluxDB.

3. Easy Integration

It speaks PromQL (Prometheus Query Language), so you can plug it into existing dashboards and alerting systems (like Grafana) without changing queries.

4. Long-Term Retention

Prometheus struggles with long-term metrics storage, but VictoriaMetrics is optimized for keeping months or years of data without performance issues.

Architecture Overview

VictoriaMetrics can be deployed in two modes:

  • Single-node: Easy to run in Docker or as a binary, great for small to medium workloads.
  • Clustered: Horizontally scalable with separate components for ingestion, storage, and querying.

Typical setup:

  • Metrics ingested from Prometheus, Graphite, or OpenTSDB.
  • Data stored in VictoriaMetrics with compression.
  • Queries run via PromQL-compatible API.
  • Visualized in Grafana dashboards.

Getting Started with VictoriaMetrics

Install via Docker (Single-node)

docker run -d -p 8428:8428 \
  --name victoriametrics \
  victoriametrics/victoria-metrics \
  -storageDataPath=/victoria-metrics-data

Access the web UI at:

http://localhost:8428

Configure Prometheus to Remote Write

In prometheus.yml:

remote_write:
  - url: http://victoriametrics:8428/api/v1/write

This way, Prometheus sends metrics to VictoriaMetrics for storage.

Who Uses VictoriaMetrics ?

  • Enterprises that outgrow Prometheus storage.
  • DevOps teams needing long-term monitoring data.
  • Cloud providers integrating monitoring into their platforms.
  • Performance engineers running large-scale benchmarks.

Key Takeaways

  • VictoriaMetrics is a high-performance, Prometheus-compatible time-series database.
  • It solves Prometheus’s long-term storage limitations with scalability and compression.
  • Ideal for DevOps, monitoring platforms, and enterprises handling large-scale metrics.
  • Works seamlessly with Grafana for visualization.

Interesting Benchmarks

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