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Airbrake vs Apache Spark MLlib

Airbrake logo

Airbrake

Logging

Error Tracking and Performance Monitoring

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: Airbrake data retention is 30 days on every plan, including the $799 a month Business tier; 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: Airbrake covers Error tracking, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where Airbrake and Apache Spark MLlib differ
AttributeAirbrakeApache Spark MLlib
Pricing modelsubscriptionopen-source
PlatformsWeb, ApiLinux, macOS, Windows
CategoryLoggingMachine Learning
Founded20081999

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 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.

Airbrake

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

Apache Spark MLlib

  • Machine learningnot Airbrake
  • Data sciencenot Airbrake
  • Distributed computingnot 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

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

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

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib 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 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 Airbrake or Apache Spark MLlib better?
Neither clearly leads. Airbrake 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, Airbrake or Apache Spark MLlib?
Airbrake starts at Free and Apache Spark MLlib at Free.
Does Airbrake or Apache Spark MLlib run on more platforms?
Airbrake runs on Web, Api. Apache Spark MLlib runs on Linux, macOS, Windows.
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 Apache Spark MLlib is typically brought in for.
What can Airbrake do that Apache Spark MLlib cannot?
Airbrake covers Error tracking, Performance monitoring, Deploy tracking, Custom notifications. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

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
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
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
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
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
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
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