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Rootly vs Apache Spark MLlib

Rootly logo

Rootly

Logging

AI-native incident management with automation, on-call, and root cause analysis

From
$20/user-month
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

  • Only Apache Spark MLlib has a free tier, so it costs nothing to try first.
  • Each has a real cost: Rootly pricing higher than some competitors for basic features; 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: Rootly covers AI SRE automation, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where Rootly and Apache Spark MLlib differ
AttributeRootlyApache Spark MLlib
Starting price$20/user-monthFree
Pricing modelsubscriptionopen-source
Free tierNoYes
PlatformsWeb, Mobile, Slack, Microsoft TeamsLinux, macOS, Windows
CategoryLoggingMachine Learning
Founded20201999

Identical on both: 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 Rootly

  • AI SRE automation
  • Alert routing
  • On-call management
  • Incident response
  • Call routing
  • AI meeting bot
  • Status pages

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.

Rootly

  • Automate on-call and incident response workflowsnot Apache Spark MLlib
  • Run root cause analysis with AI assistancenot Apache Spark MLlib
  • Track and improve Mean Time to Mitigation (MTTR)not Apache Spark MLlib
  • Coordinate response across distributed teamsnot Apache Spark MLlib
  • Learn from post-incident retrospectivesnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Rootly
  • Data sciencenot Rootly
  • Distributed computingnot Rootly

Where each one falls short

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

Rootly

  • Pricing higher than some competitors for basic features
  • AI SRE features require separate contact-sales engagement
  • Learning curve for advanced automation features
  • Per-user pricing increases costs as team grows

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

Rootly

$20/user-month
  • Incident Response Essentials$20/user-month
    • Response with Slack integration
    • @Rootly AI Chat
    • AI Similar Incidents detection
  • Incident Response Enterprise$undefined/custom
    • All Essentials features
    • Custom forms and incident types
    • Private incidents
  • On-Call Essentials$20/user-month
    • Alert grouping and routing
    • Live call routing (1 phone number)
    • Schedules and escalation policies
  • On-Call Enterprise$undefined/custom
    • All Essentials features
    • 5 phone numbers for call routing
    • Unlimited schedules

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

Which should you pick?

Choose Rootly if

  • You need ai sre automation.
  • You work on Web, Mobile, Slack, Microsoft Teams.
  • You also want alert routing.
Rootly 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 Rootly or Apache Spark MLlib better?
Neither clearly leads. Rootly starts at $20/user-month and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Rootly or Apache Spark MLlib?
Apache Spark MLlib has a free tier; the other does not. Paid plans start at $20/user-month for Rootly and Free for Apache Spark MLlib.
Does Rootly or Apache Spark MLlib run on more platforms?
Rootly runs on Web, Mobile, Slack, Microsoft Teams. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Apache Spark MLlib for free?
Yes. Apache Spark MLlib has a free tier, so you can try it without paying. Rootly starts at $20/user-month.
What is Rootly best used for?
Rootly is most often used for automate on-call and incident response workflows, run root cause analysis with ai assistance, track and improve mean time to mitigation (mttr), coordinate response across distributed teams. Of those, automate on-call and incident response workflows and run root cause analysis with ai assistance are not what Apache Spark MLlib is typically brought in for.
What can Rootly do that Apache Spark MLlib cannot?
Rootly covers AI SRE automation, Alert routing, On-call management, Incident response. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

Answered from the vendors’ own pages

Rootly: How much does Rootly cost?

Rootly charges $20/user/month for both Incident Response and On-Call Essentials plans. Enterprise plans require contacting sales. Startups under 100 employees with less than $50M raised get up to 50% discount.

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
Rootly: What is Rootly AI SRE?

AI SRE is an advanced feature that provides automated root cause analysis, alert correlation with system changes, impact analysis, and remediation suggestions. Pricing requires contact with sales.

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
Rootly: Does Rootly integrate with Slack?

Yes, Rootly natively integrates with Slack for incident response workflows, allowing teams to manage incidents directly in Slack.

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
Rootly: Are there discounts for small companies?

Yes, startups under 100 employees or less than 25 employees can get special pricing up to 50% discount. Contact Rootly sales for details.

Source
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