Softwr

Machine Learning · head to head

Dask vs Weka

Dask logo

Dask

Machine Learning

Scalable analytics in Python

From
Free
Rated
-
Full reviewWebsite
Weka logo

Weka

Machine Learning

Collection of machine learning algorithms

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dask each Dask task carries between 200 microseconds and 1 millisecond of scheduler overhead, so graphs of millions of tasks add 10 minutes to hours of pure overhead; Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • They diverge on capability: Dask covers Parallel computing, Weka covers Classification.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dask and Weka actually diverge.

Attributes where Dask and Weka differ
AttributeDaskWeka
Founded20151993

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), platforms (Linux, Mac, Windows), user rating (Not yet rated), category (Machine Learning).

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 Dask

  • Parallel computing
  • Distributed DataFrames
  • Lazy evaluation
  • Dynamic task scheduling
  • Dashboard
  • NumPy
  • Pandas
  • scikit-learn

Only in Weka

  • Classification
  • Regression
  • Clustering
  • Association rules
  • Feature selection
  • Java
  • R
  • Python

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

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

Dask

  • Scaling pandas and NumPy workloads beyond a single machine's memorynot Weka
  • Parallelising custom Python task graphsnot Weka
  • Processing larger than memory arrays and dataframes on a clusternot Weka

Weka

  • Teaching and exploring classic machine learning algorithms through a GUInot Dask
  • Running data mining experiments and preprocessing without writing codenot Dask

Where each one falls short

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

Dask

  • Each Dask task carries between 200 microseconds and 1 millisecond of scheduler overhead, so graphs of millions of tasks add 10 minutes to hours of pure overhead
  • Partition sizing is left to the user: chunks must fit several times over in worker memory, and both oversized and undersized chunks are documented failure modes
  • Embedding large locally created DataFrames or Arrays into a Dask computation is documented as a practice to avoid because of network overhead
  • Calling compute repeatedly in a loop rather than batching prevents parallelisation of queries
  • The documentation itself advises trying better algorithms, file formats or sampling before adopting Dask

Weka

  • The package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • Weka is split into a stable 3.8 branch that receives only bug fixes and compatibility-safe upgrades and a 3.9 development branch that may receive features that break compatibility
  • Weka requires a 64-bit Java VM; the bundled installers ship Bellsoft OpenJDK 25 per platform and architecture

Pricing, plan by plan

Dask

Free
  • Open SourceFree
    • Parallel computing
    • Distributed DataFrames
    • ML integration

Weka

Free
  • Open SourceFree
    • All ML algorithms
    • GUI and CLI
    • Java API

Which should you pick?

Choose Dask if

  • You need parallel computing.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want distributed dataframes.
Dask review

Choose Weka if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want regression.
Weka review

Questions people ask

Is Dask or Weka better?
Neither clearly leads. Dask starts at Free and Weka at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dask or Weka?
Dask starts at Free and Weka at Free.
Does Dask or Weka run on more platforms?
Both run on Linux, Mac, Windows, so platform support will not decide this one for you.
Can I use Dask for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dask best used for?
Dask is most often used for scaling pandas and numpy workloads beyond a single machine's memory, parallelising custom python task graphs, processing larger than memory arrays and dataframes on a cluster. Of those, scaling pandas and numpy workloads beyond a single machine's memory and parallelising custom python task graphs are not what Weka is typically brought in for.
What can Dask do that Weka cannot?
Dask covers Parallel computing, Distributed DataFrames, Lazy evaluation, Dynamic task scheduling. Weka covers Classification, Regression, Clustering, Association rules. Both handle Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

Dask: Is Dask free to use?

Yes, Dask is completely free and open source under the New-BSD License. You can install it via conda or pip at no cost.

Source
Weka: What is the cost of Weka software?

Weka is provided at no cost as open-source software released under the GNU General Public License, making it freely available for download and use.

Source
Dask: Can I use Dask for commercial applications?

Yes, the New-BSD License permits commercial use. You can deploy Dask in production environments without licensing fees.

Source
Weka: Are there commercial licensing options available?

Yes, the project offers information about commercial licenses for organizations requiring non-GPL terms, which can be found in their commercial applications documentation.

Source
Dask: Is there a managed cloud service for Dask?

Yes, Coiled is a commercial cloud service for managed Dask deployments. Coiled is free for individuals with modest use and easy to use with cloud accounts. Paid options are available for production use.

Source
Weka: What support resources are available to users?

Multiple support avenues exist including comprehensive documentation, frequently asked questions, dedicated help resources, and access to courses for learning the platform.

Source
Dask: What are typical data processing costs with Dask?

Dask users typically process cloud data at approximately $0.10 per TiB, though this reflects data transfer costs rather than Dask software licensing fees.

Source
Weka: Is source code access provided?

Yes, developers have full access to source code through the Git repository, along with development documentation and code credits for contributors.

Source
Share

Related pages

More on Dask

More on Weka

Keep looking

Other head to heads