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Dynatrace vs Apache Spark MLlib

Dynatrace logo

Dynatrace

Logging

Application Performance Management and Observability

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: Dynatrace pricing is commitment based: rates require an annual platform level commitment rather than month to month purchase; 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: Dynatrace covers AI-powered analytics, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where Dynatrace and Apache Spark MLlib differ
AttributeDynatraceApache Spark MLlib
Pricing modelsubscriptionopen-source
PlatformsWeb, ApiLinux, macOS, Windows
CategoryLoggingMachine Learning
Founded20051999

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 Dynatrace

  • AI-powered analytics
  • APM
  • Infrastructure monitoring
  • Log analysis
  • 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.

Dynatrace

  • Full stack application performance monitoring with automatic dependency discoverynot Apache Spark MLlib
  • Kubernetes and container platform observability priced per podnot Apache Spark MLlib
  • Log ingest, processing and query analyticsnot Apache Spark MLlib
  • Real user monitoring and session replay for web applicationsnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Dynatrace
  • Data sciencenot Dynatrace
  • Distributed computingnot Dynatrace

Where each one falls short

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

Dynatrace

  • Pricing is commitment based: rates require an annual platform level commitment rather than month to month purchase
  • Full-Stack Monitoring is priced at $58 per month per 8 GiB of host memory, so a 64 GiB host counts as eight units
  • Infrastructure Monitoring at $29 per host per month excludes code level tracing, which requires Full-Stack
  • Session Replay doubles Real User Monitoring cost from $2.25 to $4.50 per 1,000 sessions
  • Runtime Vulnerability Analytics and Runtime Application Protection are each charged separately at $13 per month per 8 GiB host on top of monitoring

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

Dynatrace

Free
  • FreeFree
    • AI-powered analytics
    • APM
    • Infrastructure monitoring

Apache Spark MLlib

Free

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

Which should you pick?

Choose Dynatrace if

  • You need ai-powered analytics.
  • You want to start without paying.
  • You work on Web, Api.
  • You also want apm.
Dynatrace 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 Dynatrace or Apache Spark MLlib better?
Neither clearly leads. Dynatrace 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, Dynatrace or Apache Spark MLlib?
Dynatrace starts at Free and Apache Spark MLlib at Free.
Does Dynatrace or Apache Spark MLlib run on more platforms?
Dynatrace runs on Web, Api. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Dynatrace for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dynatrace best used for?
Dynatrace is most often used for full stack application performance monitoring with automatic dependency discovery, kubernetes and container platform observability priced per pod, log ingest, processing and query analytics, real user monitoring and session replay for web applications. Of those, full stack application performance monitoring with automatic dependency discovery and kubernetes and container platform observability priced per pod are not what Apache Spark MLlib is typically brought in for.
What can Dynatrace do that Apache Spark MLlib cannot?
Dynatrace covers AI-powered analytics, APM, Infrastructure monitoring, Log analysis. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

Answered from the vendors’ own pages

Dynatrace: What is the pricing model for Dynatrace monitoring?

Dynatrace uses commitment-based platform subscription pricing with a minimum annual commitment at the platform level. You pay no per-capability or per-user fees. All capabilities are included day one and draw from your commitment at published rates.

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
Dynatrace: Is there an overage charge if I exceed my commitment?

No, there are no overage penalties. Excess usage continues at the same per-unit rates published on the rate card. The more you commit upfront, the deeper your discount.

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
Dynatrace: What is the cost for monitoring application infrastructure?

Application monitoring costs $7/month per host ($0.01/hour) for Foundation & Discovery, $29/month per host for Infrastructure Monitoring, or $58/month per 8 GiB of host memory for Full-Stack Monitoring.

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
Dynatrace: How much does log ingestion and querying cost?

Log Analytics pricing is $0.20/GiB for ingestion, then either $0.0007/GiB-day for retention with bundled queries (10-35 days retention included), or pay-per-query at $0.0007/GiB-day retention plus $0.0035 per GiB scanned.

Source
Dynatrace: Is there a free trial available?

Yes, Dynatrace offers a 15-day free trial plus a sandbox environment for hands-on exploration at no cost.

Source
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