Softwr

Software · head to head

Pachyderm vs Apache Spark MLlib

P

Pachyderm

Software

Data versioning and pipelines for production ML

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Software

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Pachyderm core software is Apache-2.0 licensed and free to self-host; 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: Pachyderm covers Data versioning, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where Pachyderm and Apache Spark MLlib differ
AttributePachydermApache Spark MLlib
Pricing modelfreemiumopen-source
PlatformsLinuxLinux, macOS, Windows
Founded20141999

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 Pachyderm

  • Data versioning
  • Data-driven pipelines
  • Automatic provenance
  • Kubernetes-native
  • Reproducibility
  • Kubernetes
  • S3
  • GCS

Only in Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

Both cover

  • Linux support

What people use each for

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

Pachyderm

  • Machine learningnot Apache Spark MLlib
  • Data analysisnot Apache Spark MLlib
  • Model trainingnot Apache Spark MLlib
  • Predictive analyticsnot Apache Spark MLlib

Apache Spark MLlib

  • Large-scale distributed machine learning on Spark clustersnot Pachyderm
  • Classification and regression with decision trees, random forests, gradient-boosted treesnot Pachyderm
  • Clustering with K-means and Gaussian Mixture Modelsnot Pachyderm

Where each one falls short

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

Pachyderm

  • Core software is Apache-2.0 licensed and free to self-host

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

Pachyderm

Free
  • CommunityFree
    • Core features
    • Community support
  • EnterpriseFree
    • Advanced security
    • Premium support
    • SLAs

Apache Spark MLlib

Free

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

Which should you pick?

Choose Pachyderm if

  • You need data versioning.
  • You want to start without paying.
  • You work on Linux.
  • You also want data-driven pipelines.
Pachyderm 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 Pachyderm or Apache Spark MLlib better?
Neither clearly leads. Pachyderm 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, Pachyderm or Apache Spark MLlib?
Pachyderm starts at Free and Apache Spark MLlib at Free.
Does Pachyderm or Apache Spark MLlib run on more platforms?
Pachyderm runs on Linux. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Pachyderm for free?
Both have a free tier, so you can try either at no cost before committing.
What is Pachyderm best used for?
Pachyderm is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Apache Spark MLlib is typically brought in for.
What can Pachyderm do that Apache Spark MLlib cannot?
Pachyderm covers Data versioning, Data-driven pipelines, Automatic provenance, Kubernetes-native. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Linux support.
ShareXLinkedInRedditWhatsAppEmail

Related pages

More on Pachyderm

More on Apache Spark MLlib

Keep looking

Other head to heads