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Databricks vs Pachyderm

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Databricks

Software

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
P

Pachyderm

Software

Data versioning and pipelines for production ML

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; Pachyderm core software is Apache-2.0 licensed and free to self-host
  • They diverge on capability: Databricks covers Delta Lake, Pachyderm covers Data versioning.

Where they differ

Only the attributes on which Databricks and Pachyderm actually diverge.

Attributes where Databricks and Pachyderm differ
AttributeDatabricksPachyderm
Pricing modelusage-basedfreemium
PlatformsWeb, Aws, Azure, GcpLinux
Founded20132014

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 Databricks

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

Only in Pachyderm

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

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 Pachyderm
  • Building a lakehouse over data in cloud object storagenot Pachyderm
  • Training and serving machine learning models alongside the datanot Pachyderm

Pachyderm

  • Machine learningnot Databricks
  • Data analysisnot Databricks
  • Model trainingnot Databricks
  • Predictive analyticsnot 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

Pachyderm

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

Pricing, plan by plan

Databricks

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

Pachyderm

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

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 Pachyderm if

  • You need data versioning.
  • You want to start without paying.
  • You work on Linux.
  • You also want data-driven pipelines.
Pachyderm review

Questions people ask

Is Databricks or Pachyderm better?
Neither clearly leads. Databricks starts at Free and Pachyderm at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or Pachyderm?
Databricks starts at Free and Pachyderm at Free.
Does Databricks or Pachyderm run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. Pachyderm 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 Pachyderm is typically brought in for.
What can Databricks do that Pachyderm cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Pachyderm covers Data versioning, Data-driven pipelines, Automatic provenance, Kubernetes-native.
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