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Machine Learning & Data Science · head to head

Databricks vs Seldon

Databricks logo

Databricks

Machine Learning & Data Science

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
Seldon logo

Seldon

Machine Learning & Data Science

Deploy, scale, and monitor machine learning models

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; Seldon production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift
  • They diverge on capability: Databricks covers Delta Lake, Seldon covers Model serving.

Where they differ

Only the attributes on which Databricks and Seldon actually diverge.

Attributes where Databricks and Seldon differ
AttributeDatabricksSeldon
Pricing modelusage-basedfreemium
PlatformsWeb, Aws, Azure, GcpLinux
Founded20132014

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).

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 Databricks

  • Delta Lake
  • Apache Spark
  • Unity Catalog
  • Photon Engine
  • Collaborative Notebooks
  • Auto-scaling
  • AWS
  • Azure

Only in Seldon

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

Both cover

  • MLflow

What people use each for

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

Databricks

  • Running Spark data engineering pipelines on managed clustersnot Seldon
  • Building a lakehouse over data in cloud object storagenot Seldon
  • Training and serving machine learning models alongside the datanot Seldon

Seldon

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

Where each one falls short

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

Databricks

  • Cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
  • The free trial lasts 14 days
  • Discounts require a Committed Use Contract, with larger commitments needed for larger discounts
  • Azure Databricks pricing is set by Microsoft rather than by Databricks
  • Security and compliance capabilities are sold as separate platform add ons rather than included in the base rate

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

Pricing, plan by plan

Databricks

Free
  • Community EditionFree
    • Limited cluster
    • Notebook environment
    • Community support
  • Standard$0.07/DBU
    • Jobs compute
    • SQL compute
    • Standard support

Seldon

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

Which should you pick?

Choose Databricks if

  • You need delta lake.
  • You want to start without paying.
  • You work on Web, Aws, Azure, Gcp.
  • You also want apache spark.
Databricks review

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

Questions people ask

Is Databricks or Seldon better?
Neither clearly leads. Databricks starts at Free and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or Seldon?
Databricks starts at Free and Seldon at Free.
Does Databricks or Seldon run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. Seldon runs on Linux.
Can I use Databricks for free?
Both have a free tier, so you can try either at no cost before committing.
What is Databricks best used for?
Databricks is most often used for running spark data engineering pipelines on managed clusters, building a lakehouse over data in cloud object storage, training and serving machine learning models alongside the data. Of those, running spark data engineering pipelines on managed clusters and building a lakehouse over data in cloud object storage are not what Seldon is typically brought in for.
What can Databricks do that Seldon cannot?
Databricks covers Delta Lake, Apache Spark, Unity Catalog, Photon Engine. Seldon covers Model serving, A/B testing, Canary deployments, Outlier detection. Both handle MLflow.
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