VictoriaMetrics
Fast, cost-efficient time-series database and monitoring drop-in for Prometheus
Overview
VictoriaMetrics is a fast, resource-efficient open-source time-series database and monitoring solution that is a drop-in replacement for Prometheus. It supports PromQL/MetricsQL, long-term storage, clustering, and high-cardinality workloads at lower cost. It is commonly used as the scalable metrics backend in a self-hosted Datadog-style stack.
Key features
- Drop-in replacement for Prometheus
- Supports PromQL and the extended MetricsQL query language
- Long-term metrics storage
- Clustering for horizontal scaling
- Efficient handling of high-cardinality workloads
Our take
VictoriaMetrics is a well-regarded time-series database that earns its reputation for being fast and resource-efficient, and its drop-in Prometheus compatibility plus PromQL/MetricsQL support means most teams can adopt it with minimal disruption. It handles long-term storage and high-cardinality data at noticeably lower cost than alternatives, and clustering is there when you outgrow a single node. The main thing to understand is scope: it's a metrics backend, not a full Datadog-style observability suite, so you'll still need to assemble dashboards, alerting, and other pieces around it. For anyone whose Prometheus setup is straining on storage or cardinality, it's a low-risk, Apache-licensed upgrade.
Ideal for: Teams running Prometheus that have hit storage, cost, or cardinality limits and need a more efficient long-term metrics backend.
Where it falls short of Datadog
- Primarily a metrics backend; needs Grafana for dashboards and vmalert for alerting
- No logs/traces/APM in the core product (separate VictoriaLogs project for logs)
- No public status page or synthetic uptime checks
- Assembling a full observability suite requires multiple components
We list the gaps honestly so you can decide if the trade-off is worth owning your data.
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