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Machine Learning & Data Science · head to head

Amazon Redshift ML vs DVC

Amazon Redshift ML logo

Amazon Redshift ML

Machine Learning & Data Science

Create machine learning models using SQL

From
Free
Rated
-
Full reviewWebsite
DVC logo

DVC

Machine Learning & Data Science

Data version control for machine learning projects

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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; DVC dVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.
  • They diverge on capability: Amazon Redshift ML covers SQL-based ML, DVC covers Data versioning.

Where they differ

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

Attributes where Amazon Redshift ML and DVC differ
AttributeAmazon Redshift MLDVC
Pricing modelusage-basedopen-source
PlatformsWebLinux, Mac, Windows
Founded20062018

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 Amazon Redshift ML

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

Only in DVC

  • Data versioning
  • Pipeline management
  • Experiment tracking
  • Remote storage
  • Git integration
  • Git
  • Azure Blob
  • Google Cloud Storage

Both cover

  • S3

What people use each for

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

Amazon Redshift ML

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

DVC

  • Machine learningnot Amazon Redshift ML
  • Data analysisnot Amazon Redshift ML
  • Model trainingnot Amazon Redshift ML
  • Predictive analyticsnot Amazon Redshift ML

Where each one falls short

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

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

DVC

  • DVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.

Pricing, plan by plan

Amazon Redshift ML

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

DVC

Free
  • Open SourceFree
    • Data versioning
    • Pipeline management
    • Experiment tracking
  • DVC StudioFree
    • Web UI
    • Team collaboration
    • Visualizations

Which should you pick?

Choose Amazon Redshift ML if

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

Choose DVC if

  • You need data versioning.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want pipeline management.
DVC review

Questions people ask

Is Amazon Redshift ML or DVC better?
Neither clearly leads. Amazon Redshift ML starts at Free and DVC at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Redshift ML or DVC?
Amazon Redshift ML starts at Free and DVC at Free.
Does Amazon Redshift ML or DVC run on more platforms?
Amazon Redshift ML runs on Web. DVC runs on Linux, Mac, Windows.
Can I use Amazon Redshift ML for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amazon Redshift ML best used for?
Amazon Redshift ML is most often used for training and running machine learning models directly from sql inside amazon redshift. Of those, training and running machine learning models directly from sql inside amazon redshift is not what DVC is typically brought in for.
What can Amazon Redshift ML do that DVC cannot?
Amazon Redshift ML covers SQL-based ML, AutoML, SageMaker integration, BYOM support. DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage. Both handle S3.
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