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Databases · head to head

Apache Pulsar vs VictoriaMetrics

Apache Pulsar logo

Apache Pulsar

Databases

Cloud-native messaging and streaming with separated storage

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: Apache Pulsar more components than Kafka: brokers, BookKeeper and ZooKeeper each need operating; VictoriaMetrics promQL compatibility is very close but not identical, and MetricsQL extensions do not port back
  • They diverge on capability: Apache Pulsar covers Separated storage, VictoriaMetrics covers PromQL compatible.
  • Prices and features above were last checked on 29 August 2026.

Where they differ

Only the attributes on which Apache Pulsar and VictoriaMetrics actually diverge.

Attributes where Apache Pulsar and VictoriaMetrics differ
AttributeApache PulsarVictoriaMetrics
CategoryDatabasesCloud

Identical on both: starting price (Free), pricing model (Open source, no licence fee), free tier (Yes), platforms (Linux, Docker, Kubernetes, Self-hosted), 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 Apache Pulsar

  • Separated storage
  • Queuing and streaming
  • Built-in multi-tenancy
  • Geo-replication

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.

Apache Pulsar

  • Platforms needing both work queues and replayable streams without running two systemsnot VictoriaMetrics
  • Multi-tenant messaging where isolation between teams is a requirementnot VictoriaMetrics
  • Deployments where storage and traffic grow at genuinely different ratesnot VictoriaMetrics

VictoriaMetrics

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

Where each one falls short

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

Apache Pulsar

  • More components than Kafka: brokers, BookKeeper and ZooKeeper each need operating
  • Correspondingly harder to run well, and the expertise is rarer than Kafka expertise
  • A much smaller ecosystem of connectors, tooling and hiring pool than Kafka
  • The architectural advantages only pay off at a scale most deployments never reach

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

Apache Pulsar

Free
  • Apache PulsarFree
    • Full functionality
    • No usage limits
    • Community support

VictoriaMetrics

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

Which should you pick?

Choose Apache Pulsar if

  • You need separated storage.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want queuing and streaming.
Apache Pulsar 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 Apache Pulsar or VictoriaMetrics better?
Neither clearly leads. Apache Pulsar 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, Apache Pulsar or VictoriaMetrics?
Apache Pulsar starts at Free and VictoriaMetrics at Free.
Does Apache Pulsar or VictoriaMetrics run on more platforms?
Both run on Linux, Docker, Kubernetes, Self-hosted, so platform support will not decide this one for you.
Can I use Apache Pulsar for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Pulsar best used for?
Apache Pulsar is most often used for platforms needing both work queues and replayable streams without running two systems, multi-tenant messaging where isolation between teams is a requirement, deployments where storage and traffic grow at genuinely different rates. Of those, platforms needing both work queues and replayable streams without running two systems and multi-tenant messaging where isolation between teams is a requirement are not what VictoriaMetrics is typically brought in for.
What can Apache Pulsar do that VictoriaMetrics cannot?
Apache Pulsar covers Separated storage, Queuing and streaming, Built-in multi-tenancy, Geo-replication. VictoriaMetrics covers PromQL compatible, Low resource use, Single binary or cluster, Remote write target.

Answered from the vendors’ own pages

Apache Pulsar: Is Apache Pulsar free?

Yes, open source under the Apache Software Foundation.

VictoriaMetrics: Is VictoriaMetrics free?

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

Apache Pulsar: Pulsar or Kafka?

Pulsar separates storage from compute and covers queuing and streaming in one system. Kafka has a far larger ecosystem and hiring pool. Most teams should have a specific reason before choosing Pulsar.

VictoriaMetrics: Does it replace Prometheus?

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

Apache Pulsar: Why does separated storage matter?

Brokers hold no data, so adding or replacing one requires no rebalancing, and storage can grow without adding serving capacity.

VictoriaMetrics: Is PromQL fully supported?

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

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