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Software · head to head

Seldon vs Apache Spark MLlib

Seldon logo

Seldon

Software

Deploy, scale, and monitor machine learning models

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: Seldon production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift; 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: Seldon covers Model serving, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where Seldon and Apache Spark MLlib differ
AttributeSeldonApache 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 Seldon

  • Model serving
  • A/B testing
  • Canary deployments
  • Outlier detection
  • Model explainability
  • Kubernetes
  • Istio
  • Prometheus

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.

Seldon

  • Serving and routing machine learning models on Kubernetesnot Apache Spark MLlib
  • Building multi-step inference pipelines with A/B tests and explainersnot Apache Spark MLlib

Apache Spark MLlib

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

Where each one falls short

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

Seldon

  • Production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift
  • The documented components carry both minimum and maximum supported versions, so newer Kubernetes and dependency versions are not automatically supported
  • Dataflow Pipelines need an additional component that the docs recommend avoiding installing when pipelines are not used
  • The Docker Compose install is offered as a lightweight alternative for environments without Kubernetes rather than as a production path

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

Seldon

Free
  • Seldon CoreFree
    • Open source
    • Kubernetes deployment
    • Model serving
  • Seldon DeployFree
    • Enterprise features
    • GUI
    • Monitoring

Apache Spark MLlib

Free

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

Which should you pick?

Choose Seldon if

  • You need model serving.
  • You want to start without paying.
  • You work on Linux.
  • You also want a/b testing.
Seldon 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 Seldon or Apache Spark MLlib better?
Neither clearly leads. Seldon 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, Seldon or Apache Spark MLlib?
Seldon starts at Free and Apache Spark MLlib at Free.
Does Seldon or Apache Spark MLlib run on more platforms?
Seldon runs on Linux. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Seldon for free?
Both have a free tier, so you can try either at no cost before committing.
What is Seldon best used for?
Seldon is most often used for serving and routing machine learning models on kubernetes, building multi-step inference pipelines with a/b tests and explainers. Of those, serving and routing machine learning models on kubernetes and building multi-step inference pipelines with a/b tests and explainers are not what Apache Spark MLlib is typically brought in for.
What can Seldon do that Apache Spark MLlib cannot?
Seldon covers Model serving, A/B testing, Canary deployments, Outlier detection. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Linux support.
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