VictoriaMetrics is a fast, cost-saving, and scalable solution for monitoring and managing time series data. It delivers high performance and reliability, making it an ideal choice for businesses of all sizes.
Here are some resources and information about VictoriaMetrics:
Yes, we open-source both the single-node VictoriaMetrics and the cluster version.
Prominent features
VictoriaMetrics is optimized for timeseries data, even when old time series are constantly replaced by new ones at a high rate, it offers a lot of features:
Long-term storage for Prometheus or as a drop-in replacement for Prometheus and Graphite in Grafana.
Powerful stream aggregation: Can be used as a StatsD alternative.
Ideal for big data: Works well with large amounts of time series data from APM, Kubernetes, IoT sensors, connected cars, industrial telemetry, financial data and various Enterprise workloads.
Query language: Supports both PromQL and the more performant MetricsQL.
Easy to setup: No dependencies, single small binary, configuration through command-line flags, but the default is also fine-tuned; backup and restore with instant snapshots.
Global query view: Multiple Prometheus instances or any other data sources may ingest data into VictoriaMetrics and queried via a single query.
Various Protocols: Support metric scraping, ingestion and backfilling in various protocol.
Contact us if you need enterprise support for VictoriaMetrics. Or you can request a free trial license here, downloaded Enterprise binaries are available at Github Releases.
We strictly apply security measures in everything we do. VictoriaMetrics has achieved security certifications for Database Software Development and Software-Based Monitoring Services. See Security page for more details.
Benchmarks
Some good benchmarks VictoriaMetrics achieved:
Minimal memory footprint: handling millions of unique timeseries with 10x less RAM than InfluxDB, up to 7x less RAM than Prometheus, Thanos or Cortex.
High data compression: 70x more data points may be stored into limited storage than TimescaleDB, 7x less storage space is required than Prometheus, Thanos or Cortex.
Reducing storage costs: 10x more effective than Graphite according to the Grammarly case study.