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Machine Learning · head to head

Dask vs SolveSpace

Dask logo

Dask

Machine Learning

Scalable analytics in Python

From
Free
Rated
-
Full reviewWebsite
S

SolveSpace

CAD

Open source parametric CAD with a constraint solver in a few megabytes

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; SolveSpace the in-house geometry kernel fails on complex boolean operations and fillets, and the failure is sometimes silent bad geometry rather than an error message, so models must be checked before export or manufacture.
  • They diverge on capability: Dask covers Parallel computing, SolveSpace covers Constraint solver.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Dask and SolveSpace actually diverge.

Attributes where Dask and SolveSpace differ
AttributeDaskSolveSpace
Pricing modelopen-sourceOpen source, no licence fee
PlatformsLinux, Mac, WindowsWindows, macOS, Linux
CategoryMachine LearningCAD
Founded2015Unknown

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 Dask

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

Only in SolveSpace

  • Constraint solver
  • Solid modelling
  • Assemblies
  • Export formats
  • Cross-platform
  • Small footprint

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 SolveSpace
  • Parallelising custom Python task graphsnot SolveSpace
  • Processing larger than memory arrays and dataframes on a clusternot SolveSpace

SolveSpace

  • Designing 3D printed parts on a machine that cannot run mainstream CADnot Dask
  • Teaching constraint-based parametric modelling without buying licences for a classroomnot Dask
  • Checking that a mechanical linkage moves as intended before cutting metalnot Dask
  • Producing dimensionally accurate STEP or STL output from a small open source toolchainnot 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

SolveSpace

  • The in-house geometry kernel fails on complex boolean operations and fillets, and the failure is sometimes silent bad geometry rather than an error message, so models must be checked before export or manufacture.
  • There is no proper drawing and dimensioning workflow, so manufacturing documentation has to be produced in another application.
  • Development is volunteer-led and intermittent; long gaps between releases are normal and there is no support contract available at any price.
  • Assembly-level import of external CAD is very limited, so it does not fit a supply chain that exchanges native or assembly-level models with suppliers.
  • The interface follows its own conventions rather than mainstream CAD ones, so existing SolidWorks or Fusion users spend time unlearning habits for a tool with a lower ceiling.

Pricing, plan by plan

Dask

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

SolveSpace

Free
  • SolveSpaceFree
    • Full application under the GPL
    • No seat limit
    • Windows, macOS and Linux builds

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 SolveSpace if

  • You need constraint solver.
  • You want to start without paying.
  • You work on Windows, macOS, Linux.
  • You also want solid modelling.
SolveSpace review

Questions people ask

Is Dask or SolveSpace better?
Neither clearly leads. Dask starts at Free and SolveSpace at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dask or SolveSpace?
Dask starts at Free and SolveSpace at Free.
Does Dask or SolveSpace run on more platforms?
Dask runs on Linux, Mac, Windows. SolveSpace runs on Windows, macOS, Linux.
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 SolveSpace is typically brought in for.
What can Dask do that SolveSpace cannot?
Dask covers Parallel computing, Distributed DataFrames, Lazy evaluation, Dynamic task scheduling. SolveSpace covers Constraint solver, Solid modelling, Assemblies, Export formats.

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
SolveSpace: Is it really free for commercial work?

Yes. It is released under the GPL with no licence fee and no seat limit. Support is community only.

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
SolveSpace: Can it replace Fusion 360 or SolidWorks?

No. It handles parts and simple assemblies well. Complex geometry, drawings and supply chain interoperability are outside its range.

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
SolveSpace: What hardware does it need?

Very little. It runs on old laptops and small Linux machines where mainstream CAD will not start.

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
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