Softwr

Logging · head to head

Airbrake vs PyTorch

Airbrake logo

Airbrake

Logging

Error Tracking and Performance Monitoring

From
Free
Rated
-
Full reviewWebsite
PyTorch logo

PyTorch

Machine Learning

Deep learning framework with dynamic computation graphs

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Airbrake data retention is 30 days on every plan, including the $799 a month Business tier; PyTorch dynamic computation graph can be less efficient for production inference than static graphs
  • They diverge on capability: Airbrake covers Error tracking, PyTorch covers Dynamic computation graphs.

Where they differ

Only the attributes on which Airbrake and PyTorch actually diverge.

Attributes where Airbrake and PyTorch differ
AttributeAirbrakePyTorch
Pricing modelsubscriptionUnknown
PlatformsWeb, ApiLinux, Windows, macOS
CategoryLoggingMachine Learning
Founded20082016

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 Airbrake

  • Error tracking
  • Performance monitoring
  • Deploy tracking
  • Custom notifications
  • API
  • Webhooks
  • REST
  • Web support

Only in PyTorch

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

What people use each for

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

Airbrake

  • Error and exception monitoring for web applicationsnot PyTorch
  • Performance monitoring alongside error trackingnot PyTorch
  • Alerting a team when a deploy introduces a spike in errorsnot PyTorch
  • Tracking errors across multiple projects in one accountnot PyTorch

PyTorch

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

Where each one falls short

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

Airbrake

  • Data retention is 30 days on every plan, including the $799 a month Business tier
  • The entry plan at $19 a month covers 25,000 errors and 7,500 events
  • Errors beyond the plan quota are billed on demand
  • Audit logs and spike forgiveness require the Pro tier
  • The lowest tier is limited to 1 user and 1 team

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

Pricing, plan by plan

Airbrake

Free
  • Tier 1 (Dev + errors)$19/month
    • 25,000 errors per month
    • 1 user
    • 1 team
  • Tier 2 (Basic + errors)$38/month
    • 100,000 errors per month
    • Unlimited users
    • 3 teams
  • Pro$76/month
    • Unlimited users
    • Unlimited teams
    • Unlimited projects
  • Tier 5 (Growth)$299/month
    • 1 million errors per month

PyTorch

Free

No published plan breakdown. See the PyTorch review.

Which should you pick?

Choose Airbrake if

  • You need error tracking.
  • You want to start without paying.
  • You work on Web, Api.
  • You also want performance monitoring.
Airbrake review

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

Questions people ask

Is Airbrake or PyTorch better?
Neither clearly leads. Airbrake starts at Free and PyTorch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Airbrake or PyTorch?
Airbrake starts at Free and PyTorch at Free.
Does Airbrake or PyTorch run on more platforms?
Airbrake runs on Web, Api. PyTorch runs on Linux, Windows, macOS.
Can I use Airbrake for free?
Both have a free tier, so you can try either at no cost before committing.
What is Airbrake best used for?
Airbrake is most often used for error and exception monitoring for web applications, performance monitoring alongside error tracking, alerting a team when a deploy introduces a spike in errors, tracking errors across multiple projects in one account. Of those, error and exception monitoring for web applications and performance monitoring alongside error tracking are not what PyTorch is typically brought in for.
What can Airbrake do that PyTorch cannot?
Airbrake covers Error tracking, Performance monitoring, Deploy tracking, Custom notifications. PyTorch covers Dynamic computation graphs, Automatic differentiation, GPU acceleration, Distributed training.

Answered from the vendors’ own pages

Airbrake: What is the lowest-cost Airbrake plan and what does it include?

Tier 1 costs $19 per month and includes 25,000 errors per month, 1 user seat, 1 team, and unlimited projects. This plan targets individual developers. A 10% discount applies when paying annually ($17.10 per month).

Source
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
Airbrake: Which Airbrake plan is marked as the best value?

The Pro plan at $76 per month is marked as Best Value. It includes unlimited users, unlimited teams, unlimited projects, audit logs, and spike forgiveness. Annual billing provides a 10% discount ($68 per month).

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
Airbrake: How many errors per month does each Airbrake tier allow?

Tier 1 allows 25,000 errors per month at $19/month. Tier 2 allows 100,000 errors at $38/month. Tier 4 allows 300,000 errors at $129/month. Tier 5 allows 1 million errors at $299/month. Tier 6 allows 5 million errors at $799/month.

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
Share

Related pages

More on Airbrake

More on PyTorch

Keep looking

Other head to heads