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Databases · head to head

Apache Kafka vs HiveMQ

Apache Kafka logo

Apache Kafka

Databases

Open-source distributed event streaming platform

From
Free
Rated
-
Full reviewWebsite
HiveMQ logo

HiveMQ

Networking

Enterprise MQTT broker for industrial IoT with a published self-managed price list

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Apache Kafka operationally heavy to self-host: brokers, storage, rebalancing and upgrades are a standing job, which is why managed Kafka is a large market; HiveMQ the Community Edition lacks clustering, persistence extensions, the control centre and all enterprise bridges, so a prototype built on it does not become production by buying support.
  • They diverge on capability: Apache Kafka covers Durable commit log, HiveMQ covers MQTT 5 and 3.1.1.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Apache Kafka and HiveMQ actually diverge.

Attributes where Apache Kafka and HiveMQ differ
AttributeApache KafkaHiveMQ
Pricing modelOpen source, no licence fee; managed services billed separatelyPer month by connections and throughput
PlatformsLinux, Windows, macOS, Self-hosted, DockerLinux, Docker, Kubernetes, Web
CategoryDatabasesNetworking

Identical on both: starting price (Free), 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 Apache Kafka

  • Durable commit log
  • Horizontal scale
  • Kafka Connect
  • Kafka Streams
  • Replication
  • Low latency

Only in HiveMQ

  • MQTT 5 and 3.1.1
  • Native clustering
  • Data Hub
  • Extension framework
  • Enterprise bridges
  • Control centre

What people use each for

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

Apache Kafka

  • Moving events between services without point-to-point couplingnot HiveMQ
  • Feeding analytics and warehouses from operational systems in near real timenot HiveMQ
  • Replaying history to rebuild state after a consumer bugnot HiveMQ
  • Buffering bursty producers ahead of slower downstream systemsnot HiveMQ

HiveMQ

  • A connected vehicle fleet where devices drop off the network for hours and sessions must survivenot Apache Kafka
  • An industrial plant bridging MQTT telemetry into Kafka without writing and operating the bridgenot Apache Kafka
  • A utility that needs message-level schema validation so one faulty firmware release cannot corrupt the data lakenot Apache Kafka
  • An IoT project that needs a self-managed broker price for a budget submission without entering a sales processnot Apache Kafka

Where each one falls short

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

Apache Kafka

  • Operationally heavy to self-host: brokers, storage, rebalancing and upgrades are a standing job, which is why managed Kafka is a large market
  • Overkill for straightforward job queues, where a simpler broker is easier to run and reason about
  • Ordering guarantees hold per partition, not per topic, and getting partitioning wrong is a common and expensive design mistake
  • The ecosystem is fragmented across the Apache project and vendor distributions, so documentation and tooling advice often assume a particular distribution

HiveMQ

  • The Community Edition lacks clustering, persistence extensions, the control centre and all enterprise bridges, so a prototype built on it does not become production by buying support.
  • The entry commercial tiers cap at ten thousand connections, and device fleets grow, so the step to Enterprise capacity pricing arrives sooner than most projects plan for.
  • It is a JVM application, so memory tuning and garbage collection behaviour become the operator’s problem at high connection counts, unlike the C-based brokers in this space.
  • Extensions are written in Java against HiveMQ’s SPI, which means custom authentication logic is locked to the platform and cannot move to another broker.
  • For simple use cases it is substantially heavier and more expensive than Mosquitto or EMQX, and small deployments frequently pay enterprise prices for clustering they never use.

Pricing, plan by plan

Apache Kafka

Free
  • Apache KafkaFree
    • Full platform
    • Kafka Connect
    • Kafka Streams

HiveMQ

Free
  • Community EditionFree
    • Apache 2.0 licence
    • MQTT 3.1.1 and 5 support
    • Single broker, no clustering
  • Launch$299/month
    • Ten thousand connections
    • Five hundred messages per second
    • Single broker deployment
  • Run$499/month
    • Ten thousand connections
    • One thousand messages per second
    • Single broker deployment
  • Enterprise$undefined/year
    • Priced by connections and throughput
    • Multi-broker and multi-site deployments
    • Distributed data intelligence

Which should you pick?

Choose Apache Kafka if

  • You need durable commit log.
  • You want to start without paying.
  • You work on Linux, Windows, macOS, Self-hosted, Docker.
  • You also want horizontal scale.
Apache Kafka review

Choose HiveMQ if

  • You need mqtt 5 and 3.1.1.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Web.
  • You also want native clustering.
HiveMQ review

Questions people ask

Is Apache Kafka or HiveMQ better?
Neither clearly leads. Apache Kafka starts at Free and HiveMQ at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Kafka or HiveMQ?
Apache Kafka starts at Free and HiveMQ at Free.
Does Apache Kafka or HiveMQ run on more platforms?
Apache Kafka runs on Linux, Windows, macOS, Self-hosted, Docker. HiveMQ runs on Linux, Docker, Kubernetes, Web.
Can I use Apache Kafka for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Kafka best used for?
Apache Kafka is most often used for moving events between services without point-to-point coupling, feeding analytics and warehouses from operational systems in near real time, replaying history to rebuild state after a consumer bug, buffering bursty producers ahead of slower downstream systems. Of those, moving events between services without point-to-point coupling and feeding analytics and warehouses from operational systems in near real time are not what HiveMQ is typically brought in for.
What can Apache Kafka do that HiveMQ cannot?
Apache Kafka covers Durable commit log, Horizontal scale, Kafka Connect, Kafka Streams. HiveMQ covers MQTT 5 and 3.1.1, Native clustering, Data Hub, Extension framework.

Answered from the vendors’ own pages

Apache Kafka: Is Apache Kafka free?

Yes. Kafka is open source under the Apache License v2 with no licence fee. Costs come from the infrastructure you run it on, or from a managed service such as Confluent Cloud.

HiveMQ: Is HiveMQ free?

The Community Edition is Apache 2.0 and free, but it has no clustering and none of the enterprise extensions.

Apache Kafka: How is Kafka different from a message queue?

A queue usually removes a message once it is consumed. Kafka keeps an ordered, durable log, so consumers track their own position and history can be replayed — which is what makes rebuilding state after a bug possible.

HiveMQ: What does the commercial version cost?

Self-managed Launch is 299 US dollars a month for ten thousand connections; Run is 499 with higher throughput.

Apache Kafka: Who uses Kafka?

The project reports use by more than 80% of the Fortune 100, with over 5 million lifetime downloads.

HiveMQ: Does it support MQTT 5?

Yes, both MQTT 5 and 3.1.1, including shared subscriptions and session expiry intervals.

Apache Kafka: Do I need to run Kafka myself?

No. Self-hosting is the operationally expensive option; managed services such as Confluent Cloud run the brokers for you and bill on throughput and storage instead.

HiveMQ: Can it bridge into Kafka?

Yes, via a commercial enterprise extension, not in the Community Edition.

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