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Databases · head to head

StarRocks vs VictoriaMetrics

StarRocks logo

StarRocks

Databases

Apache 2.0 MPP analytical database built for joins on open table formats

From
Free
Rated
-
Full reviewWebsite
VictoriaMetrics logo

VictoriaMetrics

Cloud

Fast, cost-effective time series database for metrics

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: StarRocks self-hosting is a genuine operations job: frontend and backend node roles, tablet distribution, compaction and materialised view refresh all need an owner, and there is no small-team-friendly single-binary mode.; VictoriaMetrics promQL compatibility is very close but not identical, and MetricsQL extensions do not port back
  • They diverge on capability: StarRocks covers Cost-based optimiser, VictoriaMetrics covers PromQL compatible.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which StarRocks and VictoriaMetrics actually diverge.

Attributes where StarRocks and VictoriaMetrics differ
AttributeStarRocksVictoriaMetrics
PlatformsLinux, Docker, KubernetesLinux, Docker, Kubernetes, Self-hosted
CategoryDatabasesCloud

Identical on both: starting price (Free), pricing model (Open source, no licence fee), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in StarRocks

  • Cost-based optimiser
  • Lakehouse query engine
  • Primary key tables
  • Materialised views
  • Shared-data mode
  • MySQL wire protocol

Only in VictoriaMetrics

  • PromQL compatible
  • Low resource use
  • Single binary or cluster
  • Remote write target

What people use each for

The jobs each tool is most often brought in to do.

StarRocks

  • Customer-facing analytics where queries join a fact table to several dimensions and must return in well under a secondnot VictoriaMetrics
  • Querying an Iceberg lakehouse directly without copying data into a proprietary warehouse formatnot VictoriaMetrics
  • Replacing a ClickHouse deployment that has become unmanageable because every new question needs another denormalised tablenot VictoriaMetrics
  • Real-time analytics fed by change data capture where rows must be updated in place rather than appendednot VictoriaMetrics

VictoriaMetrics

  • Keeping months or years of Prometheus metrics without the memory costnot StarRocks
  • High-cardinality metrics where Prometheus strugglesnot StarRocks
  • Consolidating metrics from many Prometheus instances into one queryable storenot StarRocks

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

StarRocks

  • Self-hosting is a genuine operations job: frontend and backend node roles, tablet distribution, compaction and materialised view refresh all need an owner, and there is no small-team-friendly single-binary mode.
  • CelerData is by far the dominant contributor despite Linux Foundation stewardship, so the practical roadmap risk is the same as any single-vendor open source project.
  • It inherits a MySQL-flavoured SQL dialect from its Doris ancestry, so queries written for PostgreSQL, Snowflake or Trino need rewriting rather than porting.
  • Ecosystem support is thinner than ClickHouse or Trino: fewer client libraries, fewer managed hosting options and a much smaller pool of engineers who have run it in production.
  • Memory pressure under concurrent large joins is a common production failure, and the tuning knobs for query memory limits are unforgiving compared with a cloud warehouse that just scales.

VictoriaMetrics

  • PromQL compatibility is very close but not identical, and MetricsQL extensions do not port back
  • Smaller community than Prometheus, so fewer guides and third-party integrations
  • The clustered version has meaningfully more moving parts than the single binary suggests
  • Some enterprise features sit outside the open-source offering

Pricing, plan by plan

StarRocks

Free
  • StarRocksFree
    • Apache 2.0 licence
    • Linux Foundation governance
    • No usage or node limits
  • CelerData Cloud$undefined/year
    • Managed StarRocks from the primary contributor
    • BYOC and serverless deployment options
    • Enterprise support and SLAs

VictoriaMetrics

Free
  • VictoriaMetricsFree
    • Full functionality
    • No data limits
    • Community support

Which should you pick?

Choose StarRocks if

  • You need cost-based optimiser.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want lakehouse query engine.
StarRocks review

Choose VictoriaMetrics if

  • You need promql compatible.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want low resource use.
VictoriaMetrics review

Questions people ask

Is StarRocks or VictoriaMetrics better?
Neither clearly leads. StarRocks starts at Free and VictoriaMetrics at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, StarRocks or VictoriaMetrics?
StarRocks starts at Free and VictoriaMetrics at Free.
Does StarRocks or VictoriaMetrics run on more platforms?
StarRocks runs on Linux, Docker, Kubernetes. VictoriaMetrics runs on Linux, Docker, Kubernetes, Self-hosted.
Can I use StarRocks for free?
Both have a free tier, so you can try either at no cost before committing.
What is StarRocks best used for?
StarRocks is most often used for customer-facing analytics where queries join a fact table to several dimensions and must return in well under a second, querying an iceberg lakehouse directly without copying data into a proprietary warehouse format, replacing a clickhouse deployment that has become unmanageable because every new question needs another denormalised table, real-time analytics fed by change data capture where rows must be updated in place rather than appended. Of those, customer-facing analytics where queries join a fact table to several dimensions and must return in well under a second and querying an iceberg lakehouse directly without copying data into a proprietary warehouse format are not what VictoriaMetrics is typically brought in for.
What can StarRocks do that VictoriaMetrics cannot?
StarRocks covers Cost-based optimiser, Lakehouse query engine, Primary key tables, Materialised views. VictoriaMetrics covers PromQL compatible, Low resource use, Single binary or cluster, Remote write target.

Answered from the vendors’ own pages

StarRocks: Is StarRocks open source?

Yes, Apache 2.0, governed under the Linux Foundation since 2023.

VictoriaMetrics: Is VictoriaMetrics free?

The open-source version is free with no data limits. An enterprise edition and cloud service are paid.

StarRocks: How does it differ from ClickHouse?

StarRocks is built for joins across a star schema with a cost-based optimiser; ClickHouse is fastest on denormalised single tables.

VictoriaMetrics: Does it replace Prometheus?

It can, but most teams keep Prometheus for scraping and use VictoriaMetrics as the long-term store behind it.

StarRocks: Who maintains it?

CelerData, formerly StarRocks Inc, is the dominant contributor and sells the managed service.

VictoriaMetrics: Is PromQL fully supported?

Very nearly. It implements PromQL and extends it with MetricsQL, though a small number of edge-case behaviours differ.

StarRocks: Can it query Iceberg tables directly?

Yes, along with Hudi, Delta Lake, Hive and Paimon, with a local cache for repeat queries.

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