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Machine Learning & Data Science · head to head

Databricks vs Amazon Redshift ML

Databricks logo

Databricks

Machine Learning & Data Science

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning & Data Science

Create machine learning models using SQL

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; Amazon Redshift ML free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million
  • They diverge on capability: Databricks covers Delta Lake, Amazon Redshift ML covers SQL-based ML.

Where they differ

Only the attributes on which Databricks and Amazon Redshift ML actually diverge.

Attributes where Databricks and Amazon Redshift ML differ
AttributeDatabricksAmazon Redshift ML
PlatformsWeb, Aws, Azure, GcpWeb
Founded20132006

Identical on both: starting price (Free), pricing model (usage-based), 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
  • MLflow
  • Unity Catalog
  • Photon Engine
  • Collaborative Notebooks
  • Auto-scaling
  • AWS

Only in Amazon Redshift ML

  • SQL-based ML
  • AutoML
  • SageMaker integration
  • BYOM support
  • In-database predictions
  • Amazon Redshift
  • SageMaker
  • S3

Both cover

  • Web support

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

Amazon Redshift ML

  • Training and running machine learning models directly from SQL inside Amazon Redshiftnot 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

Amazon Redshift ML

  • Free tier covers only two CREATE MODEL requests per month for two months, capped at 100,000 cells per request; beyond that training is metered at $20 per million cells for the first 10 million, dropping in tiers to $7 per million cells over 100 million

Pricing, plan by plan

Databricks

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

Amazon Redshift ML

Free
  • Free TrialFree
    • 2-month trial
    • 750 DC2.Large hours
  • On-Demand$0.25/hour
    • Per-node pricing
    • SageMaker training

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 Amazon Redshift ML if

  • You need sql-based ml.
  • You want to start without paying.
  • You also want automl.
Amazon Redshift ML review

Questions people ask

Is Databricks or Amazon Redshift ML better?
Neither clearly leads. Databricks starts at Free and Amazon Redshift ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databricks or Amazon Redshift ML?
Databricks starts at Free and Amazon Redshift ML at Free.
Does Databricks or Amazon Redshift ML run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. Amazon Redshift ML runs on Web.
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 Amazon Redshift ML is typically brought in for.
What can Databricks do that Amazon Redshift ML cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Amazon Redshift ML covers SQL-based ML, AutoML, SageMaker integration, BYOM support. Both handle Web support.
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