- Full [PromQL](https://prometheus.io/docs/prometheus/latest/querying/basics/) support. Additionally, VictoriaMetrics extends PromQL with useful features. See [Extended PromQL](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/ExtendedPromQL) for more details.
- Simple configuration. Just copy-n-paste remote storage URL to Prometheus config and that's it! See [Quick Start](https://github.com/VictoriaMetrics/VictoriaMetrics/wiki/Quick-Start) for more info.
- Reduced maintenance overhead. Prometheus local storage retention may be set to the minimum possible value - `--storage.tsdb.retention=2h` - when using VictoriaMetrics remote storage. This effectively makes Prometheus stateless, so it may be run as a stateless service in Kubernetes.
- Insertion rate scales to millions of metric values per second.
- Storage scales to millions of metrics with trillions of metric values.
- Wide range of retention periods - from 1 month to 5 years. Users may create different projects (aka `storage namespaces`) with different retention periods.
- Fast query engine. It excels on heavy queries over thousands of metrics with millions of metric values.
- The lowest price on the market. We can afford this thanks to cost-effective VictoriaMetrics core.
- The same remote storage URL may be used by multiple Prometheus instances collecting distinct metric sets, so all these metrics may be used in a single query (aka `global querying view`). This works ideally for multiple Prometheus instances located in different subnetworks / datacenters.
