VictoriaMetrics is free!

VictoriaMetrics – high-performance, cost-effective and scalable time series database, long-term remote storage for Prometheus https://victoriametrics.com/

VictoriaMetrics on GitHub, writen in Go 🙂

Prominent features

• Supports Prometheus querying API, so it can be used as Prometheus drop-in replacement in Grafana. Additionally, VictoriaMetrics extends PromQL with opt-in useful features.
• High performance and good scalability for both inserts and selects. Outperforms InfluxDB and TimescaleDB by up to 20x.
• Uses 10x less RAM than InfluxDB when working with millions of unique time series (aka high cardinality).
• High data compression, so up to 70x more data points may be crammed into a limited storage comparing to TimescaleDB.
• Optimized for storage with high-latency IO and low iops (HDD and network storage in AWS, Google Cloud, Microsoft Azure, etc). See graphs from these benchmarks.
• A single-node VictoriaMetrics may substitute moderately sized clusters built with competing solutions such as Thanos, Uber M3, Cortex, InfluxDB or TimescaleDB. See vertical scalability benchmarks.
• Easy operation:
  • VictoriaMetrics consists of a single executable without external dependencies.
  • All the configuration is done via explicit command-line flags with reasonable defaults.
  • All the data is stored in a single directory pointed by -storageDataPath flag.
  • Easy backups from instant snapshots.
• Storage is protected from corruption on unclean shutdown (i.e. hardware reset or kill -9) thanks to the storage architecture.
• Supports metrics‘ ingestion and backfilling via the following protocols:
  • Prometheus remote write API
  • InfluxDB line protocol
  • Graphite plaintext protocol with tags if -graphiteListenAddr is set.
  • OpenTSDB put message if -opentsdbListenAddr is set.
• Ideally works with big amounts of time series data from Kubernetes, IoT sensors, connected cars and industrial telemetry.
• Has open source cluster version.