VictoriaMetrics

Fast, cost-effective time series database and monitoring solution built for high-cardinality metrics at scale. Uses an optimized storage engine with strong compression, supports Prometheus-compatible scraping and querying, and runs as a single binary for simplified deployment.

VictoriaMetrics is trusted by organizations such as CERN, Grammarly, Cornell University, Spotify, and Brandwatch. It acts as a drop-in replacement for Prometheus with full API compatibility: existing scrapers, Grafana dashboards, and PromQL queries work without changes. Users often report lower storage and compute costs compared to Prometheus and InfluxDB, especially at high time series cardinality.

Key features:

• Prometheus-compatible ingestion, query API, and PromQL with MetricsQL extensions
• Single-binary deployment with built-in scraping, alerting, and dashboards via VMUI
• OpenTelemetry and Grafana integration, plus support for InfluxDB, Graphite, and OpenTSDB protocols
• Kubernetes operator and Helm charts for cloud-native deployment
• Optional cluster mode, downsampling, and long-term retention

Ideal for teams scaling beyond Prometheus limits or looking to consolidate metrics storage. Use it for infrastructure monitoring in Kubernetes clusters, application metrics from microservices, IoT and sensor data at high ingest rates, and observability stacks that need logs and traces alongside metrics.