VictoriaMetrics
VictoriaMetrics is an open-source time series database and monitoring solution written in Go, designed as a cost-effective alternative or complement to Prometheus. It supports ingestion from multiple metric sources, scales horizontally via clustering, and offers both community (Apache 2.0) and enterprise editions with advanced features like anomaly detection and downsampling.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | VictoriaMetrics/VictoriaMetrics |
| Owner | VictoriaMetrics |
| Primary language | Go |
| License | Apache-2.0 — OSI-approved |
| Stars | 17.3k |
| Forks | 1.7k |
| Open issues | 775 |
| Latest release | v1.147.0 (2026-07-06) |
| Last updated | 2026-07-08 |
| Source | https://github.com/VictoriaMetrics/VictoriaMetrics |
What VictoriaMetrics is
Built in Go, VictoriaMetrics provides a TSDB optimized for high-cardinality metric workloads, supporting PromQL and its own MetricsQL query language. It ingests via Prometheus remote-write, InfluxDB line protocol, Graphite, OpenTSDB, OpenTelemetry, and others; deployment modes include single-node and distributed cluster architecture with optional NFS storage backend.
Get the VictoriaMetrics source
Clone the repository and explore it locally.
git clone https://github.com/VictoriaMetrics/VictoriaMetrics.gitcd VictoriaMetrics# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- VictoriaMetrics runs as a single small binary with no external dependencies; default configuration is production-ready but requires review of retention policy, resource allocation (RAM for in-memory indexing), and backup strategy.
- Cluster deployment requires additional operational complexity: vminsert, vmstorage, and vmselect components must be managed separately, though scaling is linear. Single-node setup is simpler for sub-100M metric/sec workloads.
- Data ingestion protocol choice affects client library selection and metric format; validate exporter/SDK compatibility for your monitoring stack (Prometheus remote-write is most common, but InfluxDB/Graphite/OpenTelemetry also supported).
- Backup and restore use point-in-time snapshots, reducing downtime vs. traditional export/import; however, snapshot management and storage strategy must be planned upfront (local, NFS, or cloud storage).
- Query language: PromQL compatibility is high but not 100%; MetricsQL offers additional functions. Grafana dashboards typically work with minimal changes; review custom Prometheus-specific queries.
When to avoid it — and what to weigh
- Heavy reliance on third-party integrations not listed — If your ecosystem depends on integrations or exporters not explicitly documented (Prometheus, Grafana, Kubernetes, etc.), validate compatibility before committing; VictoriaMetrics supports major tools but custom or niche integrations may require engineering effort.
- Strict requirement for on-premises, air-gapped deployments without external audit — While VictoriaMetrics can run on-premises, enterprise features (anomaly detection, backup automation, LTS) are primarily available as commercial offerings; if you need these without vendor involvement, community version may be limiting.
- Zero operational overhead or fully managed SaaS requirement — VictoriaMetrics is self-hosted and requires infrastructure provisioning, backup strategy, and monitoring. For teams seeking zero-ops, managed alternatives (Datadog, New Relic, Grafana Cloud) may be preferable.
- Complex transaction semantics or ACID compliance for metrics — VictoriaMetrics is optimized for append-only time series and does not provide transactional guarantees typical of relational databases; if your use case demands ACID semantics, consider a different architecture.
License & commercial use
VictoriaMetrics is licensed under Apache License 2.0 (Apache-2.0), a permissive open-source license that permits commercial use, modification, and distribution with minimal restrictions. Both single-node and cluster versions are covered by this license.
Apache 2.0 permits commercial deployment and use without licensing fees. However, enterprise features (anomaly detection, backup automation, multiple retentions, downsampling, stable LTS releases) require a separate commercial contract or trial license from VictoriaMetrics Inc. Consult their enterprise sales ([email protected]) to clarify which features are included in your use case.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Strong |
| Assessment confidence | High |
VictoriaMetrics claims security certifications for Database Software Development and Software-Based Monitoring Services, but specific certification bodies, audit scope, and dates are not provided in the data. Review required: authentication/authorization mechanisms (data suggests none in community version), encryption in transit and at rest, secret management for remote-write credentials, and network isolation in cluster deployments. Single-node deployments expose metrics endpoint by default; restrict access via firewall or reverse proxy in untrusted networks.
Alternatives to consider
Prometheus (single-node + optional Thanos)
Native Prometheus is simpler for small workloads; Thanos adds clustering and long-term storage but adds operational overhead. VictoriaMetrics combines both in one simpler package, though Prometheus remains the de-facto standard.
InfluxDB (open-source or Cloud)
InfluxDB is purpose-built TSDB with strong query language (Flux/InfluxQL) and native clustering, but typically higher resource costs. VictoriaMetrics claims better compression and cost efficiency for high-cardinality workloads.
Datadog, Grafana Cloud, or New Relic (SaaS)
Managed alternatives eliminate operational burden and include alerting, dashboards, and advanced features out-of-box, but incur per-metric-unit costs and vendor lock-in. VictoriaMetrics is self-hosted and cheaper at scale for cost-conscious teams.
Build on VictoriaMetrics with DEV.co software developers
VictoriaMetrics is production-ready for teams seeking cost-effective, scalable time series storage. Start with single-node deployment, use Prometheus remote-write for immediate integration, and scale to cluster architecture as needed. Review enterprise features and security certifications with the VictoriaMetrics team if compliance or advanced features are required.
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VictoriaMetrics FAQ
Can VictoriaMetrics replace Prometheus entirely?
What is the cost comparison to Prometheus + object storage?
Is there a managed/SaaS version of VictoriaMetrics?
Do I need enterprise version for production?
Software development & web development with DEV.co
Adopting VictoriaMetrics is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate open-source databases software in production.
Evaluate VictoriaMetrics for Your Monitoring Stack
VictoriaMetrics is production-ready for teams seeking cost-effective, scalable time series storage. Start with single-node deployment, use Prometheus remote-write for immediate integration, and scale to cluster architecture as needed. Review enterprise features and security certifications with the VictoriaMetrics team if compliance or advanced features are required.