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Machine Learning · head to head

Alteryx vs Azure Machine Learning

Alteryx logo

Alteryx

Machine Learning

Analytics automation platform

From
$250/month
Rated
-
Full reviewWebsite
Azure Machine Learning logo

Azure Machine Learning

Machine Learning

Microsoft's managed platform for training, tracking and deploying models on Azure

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Azure Machine Learning has a free tier, so it costs nothing to try first.
  • Each has a real cost: Alteryx starter is $250 per user per month billed annually, and the Professional and Enterprise editions are quote-only; Azure Machine Learning managed online endpoints are billed per underlying virtual machine for as long as the deployment exists, with no scale to zero, so a model answering a handful of requests a day costs the same as one answering thousands.
  • They diverge on capability: Alteryx covers Data preparation, Azure Machine Learning covers Workspace.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Alteryx and Azure Machine Learning actually diverge.

Attributes where Alteryx and Azure Machine Learning differ
AttributeAlteryxAzure Machine Learning
Starting price$250/monthFree
Pricing modelsubscriptionusage-based
Free tierNoYes
PlatformsWindows, WebAzure Cloud
Founded19971975

Identical on both: user rating (Not yet rated), category (Machine Learning).

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 Alteryx

  • Data preparation
  • Data blending
  • Predictive analytics
  • Spatial analytics
  • Reporting
  • Python
  • R
  • Snowflake

Only in Azure Machine Learning

  • Workspace
  • Compute clusters
  • MLflow-compatible tracking
  • Model registry
  • Managed online endpoints
  • Batch endpoints
  • Automated machine learning
  • Pipelines

What people use each for

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

Alteryx

  • Data preparation and building AI-ready datasetsnot Azure Machine Learning
  • Predictive analytics without writing codenot Azure Machine Learning
  • Automating and orchestrating repeatable analytics workflowsnot Azure Machine Learning
  • Enterprise reporting with governed, reusable logicnot Azure Machine Learning
  • Connecting to Snowflake, Databricks and cloud warehouses alongside on-premises systemsnot Azure Machine Learning

Azure Machine Learning

  • Enterprises standardised on Azure where using a different cloud for machine learning would mean a fresh security and compliance reviewnot Alteryx
  • Training that needs to burst onto a GPU cluster occasionally without buying hardware, with the cluster scaling back to zero afterwardsnot Alteryx
  • Regulated workloads that must stay inside a virtual network with private endpoints and auditable role-based accessnot Alteryx
  • Teams already using MLflow who want the tracking interface they know backed by a managed service and enterprise identitynot Alteryx

Where each one falls short

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

Alteryx

  • Starter is $250 per user per month billed annually, and the Professional and Enterprise editions are quote-only
  • Automation runs are metered, with 50 included on Starter and 15,000 on Professional, and more must be bought
  • Cost depends on three separate dimensions at once: edition, user role and automation capacity
  • Advanced analytics, governance and orchestration are withheld from the entry edition

Azure Machine Learning

  • Managed online endpoints are billed per underlying virtual machine for as long as the deployment exists, with no scale to zero, so a model answering a handful of requests a day costs the same as one answering thousands.
  • GPU capacity is governed by per-region, per-family quota that must be requested and approved, so a training plan can be blocked by an administrative ticket rather than by budget, and the newest accelerators are often unavailable in the region your data is required to stay in.
  • The v2 Python SDK and command line use a different object model from v1 and code, pipelines and examples written for v1 do not port mechanically, which has left teams maintaining two ways of doing the same thing and searching documentation that mixes both.
  • The workspace binds storage, key vault, container registry and compute together, so recreating or moving one is not a light operation, and configuring it properly with private endpoints and a managed virtual network is a multi-day job for somebody who already knows Azure networking.
  • Experiment history, registered models, environments, endpoints and pipeline definitions live inside the workspace, and although the tracking interface is MLflow-compatible, moving the accumulated lineage and orchestration elsewhere is a rebuild, so the cost of leaving grows every month the team uses it.

Pricing, plan by plan

Alteryx

$250/month
  • Starter Edition$250/month
    • 1-10 users
    • 50 automation runs included
    • Cloud only
  • Professional Edition$null/month
    • Basic and Full users
    • 15,000 automation runs included
    • Cloud and desktop deployment
  • Enterprise Edition$null/month
    • All user types
    • 15,000 automation runs included
    • All deployment options

Azure Machine Learning

Free
  • Free TierFree
    • Limited compute
    • Basic features
  • Pay-as-you-go$0.05/hour
    • Full platform
    • All compute options
    • Enterprise features

Which should you pick?

Choose Alteryx if

  • You need data preparation.
  • You work on Windows, Web.
  • You also want data blending.
Alteryx review

Choose Azure Machine Learning if

  • You need workspace.
  • You want to start without paying.
  • You work on Azure Cloud.
  • You also want compute clusters.
Azure Machine Learning review

Questions people ask

Is Alteryx or Azure Machine Learning better?
Neither clearly leads. Alteryx starts at $250/month and Azure Machine Learning at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Alteryx or Azure Machine Learning?
Azure Machine Learning has a free tier; the other does not. Paid plans start at $250/month for Alteryx and Free for Azure Machine Learning.
Does Alteryx or Azure Machine Learning run on more platforms?
Alteryx runs on Windows, Web. Azure Machine Learning runs on Azure Cloud.
Can I use Azure Machine Learning for free?
Yes. Azure Machine Learning has a free tier, so you can try it without paying. Alteryx starts at $250/month.
What is Alteryx best used for?
Alteryx is most often used for data preparation and building ai-ready datasets, predictive analytics without writing code, automating and orchestrating repeatable analytics workflows, enterprise reporting with governed, reusable logic. Of those, data preparation and building ai-ready datasets and predictive analytics without writing code are not what Azure Machine Learning is typically brought in for.
What can Alteryx do that Azure Machine Learning cannot?
Alteryx covers Data preparation, Data blending, Predictive analytics, Spatial analytics. Azure Machine Learning covers Workspace, Compute clusters, MLflow-compatible tracking, Model registry.

Answered from the vendors’ own pages

Alteryx: How much does Alteryx Starter cost?

Alteryx Starter Edition costs $250 USD per user per month when billed annually, for teams of 1-10 users.

Source
Azure Machine Learning: Is there a charge for the workspace itself?

No charge for the workspace resource. You pay for the compute it runs, the storage it uses, the container registry, key vault and any endpoints left running, which is where essentially the whole bill comes from.

Alteryx: Is there a free trial for Alteryx?

Yes, Alteryx offers a 30-day free trial to evaluate the platform before committing to a paid plan.

Source
Azure Machine Learning: Does it work with MLflow?

Yes. The tracking interface is MLflow-compatible, so existing logging code generally works unchanged, and that compatibility is the least locked-in part of the platform.

Alteryx: What differentiates Alteryx Professional from Starter?

Professional Edition supports both Basic and Full user roles, includes 15,000 automation runs, offers cloud and desktop deployment, connects to 100+ data sources, and enables advanced data preparation and macros. Professional and Enterprise editions require contacting sales for pricing.

Source
Azure Machine Learning: What is the difference between SDK v1 and v2?

A different object model and a different way of expressing jobs, components and endpoints. v2 is the current one. v1 code does not translate mechanically and a lot of material found online still assumes v1, which is a common source of wasted time.

Azure Machine Learning: Do endpoints scale to zero?

Managed online endpoints do not; they hold their virtual machines. Batch endpoints only consume compute while a job runs, so intermittent workloads are much cheaper served as batch where the use case allows it.

Azure Machine Learning: Do I need an ML engineer to run it?

For the data science work, not necessarily. For the workspace itself, yes, somebody has to understand Azure identity, networking, quota and cost management, and on teams without that person the platform becomes the bottleneck rather than the model.

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