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PyTorch vs Redash

PyTorch logo

PyTorch

Software

Deep learning framework with dynamic computation graphs

From
Free
Rated
-
Full reviewWebsite
Redash logo

Redash

Software

Connect and visualize your data

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: PyTorch dynamic computation graph can be less efficient for production inference than static graphs; Redash a basic self-hosted deployment needs a minimum of 4GB of RAM, and more RAM and CPU as background workers and API processes grow
  • They diverge on capability: PyTorch covers Dynamic computation graphs, Redash covers SQL Query Editor.

Where they differ

Only the attributes on which PyTorch and Redash actually diverge.

Attributes where PyTorch and Redash differ
AttributePyTorchRedash
Pricing modelUnknownfreemium
PlatformsLinux, Windows, macOSWeb, Self-hosted, Cloud
Founded20162013

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

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 PyTorch

  • Dynamic computation graphs
  • Automatic differentiation
  • GPU acceleration
  • Distributed training
  • TorchScript
  • TorchVision
  • TorchText
  • TorchAudio

Only in Redash

  • SQL Query Editor
  • Multiple Data Sources
  • Visualizations
  • Dashboards
  • Alerts
  • PostgreSQL
  • MySQL
  • BigQuery

What people use each for

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

PyTorch

  • Machine learningnot Redash
  • Data analysisnot Redash
  • Model trainingnot Redash
  • Predictive analyticsnot Redash

Redash

  • Self-hosted SQL query editor and dashboarding over existing databasesnot PyTorch
  • Sharing scheduled query results with a team without buying a BI licencenot PyTorch

Where each one falls short

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

PyTorch

  • Dynamic computation graph can be less efficient for production inference than static graphs
  • Requires more manual code for distributed training compared to some alternatives
  • Documentation focused heavily on research use cases rather than production deployment

Redash

  • A basic self-hosted deployment needs a minimum of 4GB of RAM, and more RAM and CPU as background workers and API processes grow
  • The official Docker images were not updated for V10, so the documented route is to deploy a V8 instance and then upgrade it
  • Anyone not using a provided cloud image has to configure the environment variables and secrets by hand

Pricing, plan by plan

PyTorch

Free

No published plan breakdown. See the PyTorch review.

Redash

Free
  • Open SourceFree
    • Full Features
    • Self-hosted
    • Community Support
  • Cloud$49/month
    • Managed Hosting
    • Automatic Updates
    • Support

Which should you pick?

Choose PyTorch if

  • You need dynamic computation graphs.
  • You want to start without paying.
  • You work on Linux, Windows, macOS.
  • You also want automatic differentiation.
PyTorch review

Choose Redash if

  • You need sql query editor.
  • You want to start without paying.
  • You work on Web, Self-hosted, Cloud.
  • You also want multiple data sources.
Redash review

Questions people ask

Is PyTorch or Redash better?
Neither clearly leads. PyTorch starts at Free and Redash at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, PyTorch or Redash?
PyTorch starts at Free and Redash at Free.
Does PyTorch or Redash run on more platforms?
PyTorch runs on Linux, Windows, macOS. Redash runs on Web, Self-hosted, Cloud.
Can I use PyTorch for free?
Both have a free tier, so you can try either at no cost before committing.
What is PyTorch best used for?
PyTorch is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Redash is typically brought in for.
What can PyTorch do that Redash cannot?
PyTorch covers Dynamic computation graphs, Automatic differentiation, GPU acceleration, Distributed training. Redash covers SQL Query Editor, Multiple Data Sources, Visualizations, Dashboards.

Answered from the vendors’ own pages

PyTorch: Is PyTorch free and open source?

Yes. PyTorch is an open source machine learning framework that is completely free to use. It was originally created and open-sourced by Facebook (now Meta) in 2016.

Source
PyTorch: What platforms does PyTorch support?

PyTorch supports Linux, Windows, and macOS. It provides strong GPU acceleration through CUDA and other backends for high-performance computing.

Source
PyTorch: Can I use PyTorch for production deployments?

Yes. PyTorch provides graph-based execution, distributed training, mobile deployment, and quantization features to support production deployments.

Source
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