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Apache Kafka vs Apache Spark MLlib

Apache Kafka logo

Apache Kafka

Databases

Open-source distributed event streaming platform

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning

Scalable machine learning on Apache Spark

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; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: Apache Kafka covers Durable commit log, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which Apache Kafka and Apache Spark MLlib actually diverge.

Attributes where Apache Kafka and Apache Spark MLlib differ
AttributeApache KafkaApache Spark MLlib
Pricing modelOpen source, no licence fee; managed services billed separatelyopen-source
PlatformsLinux, Windows, macOS, Self-hosted, DockerLinux, macOS, Windows
CategoryDatabasesMachine Learning
FoundedUnknown1999

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 Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

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 Apache Spark MLlib
  • Feeding analytics and warehouses from operational systems in near real timenot Apache Spark MLlib
  • Replaying history to rebuild state after a consumer bugnot Apache Spark MLlib
  • Buffering bursty producers ahead of slower downstream systemsnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Apache Kafka
  • Data sciencenot Apache Kafka
  • Distributed computingnot 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

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

Pricing, plan by plan

Apache Kafka

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

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

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 Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is Apache Kafka or Apache Spark MLlib better?
Neither clearly leads. Apache Kafka starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Kafka or Apache Spark MLlib?
Apache Kafka starts at Free and Apache Spark MLlib at Free.
Does Apache Kafka or Apache Spark MLlib run on more platforms?
Apache Kafka runs on Linux, Windows, macOS, Self-hosted, Docker. Apache Spark MLlib runs on Linux, macOS, Windows.
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 Apache Spark MLlib is typically brought in for.
What can Apache Kafka do that Apache Spark MLlib cannot?
Apache Kafka covers Durable commit log, Horizontal scale, Kafka Connect, Kafka Streams. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

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.

Apache Spark MLlib: How much does Apache Spark MLlib cost?

MLlib is completely free and open source, licensed under the Apache License Version 2.0. There are no subscription, licensing, or usage fees.

Source
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.

Apache Spark MLlib: What licensing does MLlib use?

MLlib is licensed under Apache License Version 2.0, making it freely available for all users regardless of organization size or use case.

Source
Apache Kafka: Who uses Kafka?

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

Apache Spark MLlib: How do I use MLlib?

MLlib is built into Apache Spark. Download Spark, which includes MLlib as a module, and deploy on your choice of infrastructure including Hadoop, Mesos, Kubernetes, standalone, or cloud.

Source
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.

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