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Machine Learning · head to head

Azure Machine Learning vs Sourcegraph Cody

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
Sourcegraph Cody logo

Sourcegraph Cody

AI

Enterprise AI coding assistant with whole-codebase context

From
$59/month
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: 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.; Sourcegraph Cody no longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
  • They diverge on capability: Azure Machine Learning covers Workspace, Sourcegraph Cody covers Multi-repository context.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Azure Machine Learning and Sourcegraph Cody differ
AttributeAzure Machine LearningSourcegraph Cody
Starting priceFree$59/month
Pricing modelusage-basedquote
Free tierYesNo
PlatformsAzure Cloudweb, windows, mac, linux
CategoryMachine LearningAI
Founded19752013

Identical on both: user rating (Not yet rated).

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 Azure Machine Learning

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

Only in Sourcegraph Cody

  • Multi-repository context
  • Large context window
  • Context filters
  • Model flexibility
  • IDE integration

What people use each for

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

Azure Machine Learning

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

Sourcegraph Cody

  • Cross-repository code understanding for large engineering orgsnot Azure Machine Learning
  • AI-assisted code review and refactoring at enterprise scalenot Azure Machine Learning
  • Enforcing data-boundary controls when using third-party LLMsnot Azure Machine Learning
  • Codebase-aware chat and autocomplete for developersnot Azure Machine Learning

Where each one falls short

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

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.

Sourcegraph Cody

  • No longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
  • Priced substantially higher than many competing AI coding assistants, with Enterprise plans typically requiring annual contracts
  • Sourcegraph has shifted its individual-developer focus to a separate product, Amp, creating uncertainty about Cody's long-term product priority
  • Requires integration with Sourcegraph's broader code intelligence platform rather than working as a lightweight standalone extension

Pricing, plan by plan

Azure Machine Learning

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

Sourcegraph Cody

$59/month
  • Enterprise$59/month
    • Whole-codebase AI context
    • Context filters for sensitive code
    • Multi-repository analysis

Which should you pick?

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

Choose Sourcegraph Cody if

  • You need multi-repository context.
  • You work on web, windows, mac, linux.
  • You also want large context window.
Sourcegraph Cody review

Questions people ask

Is Azure Machine Learning or Sourcegraph Cody better?
Neither clearly leads. Azure Machine Learning starts at Free and Sourcegraph Cody at $59/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Azure Machine Learning or Sourcegraph Cody?
Azure Machine Learning has a free tier; the other does not. Paid plans start at Free for Azure Machine Learning and $59/month for Sourcegraph Cody.
Does Azure Machine Learning or Sourcegraph Cody run on more platforms?
Azure Machine Learning runs on Azure Cloud. Sourcegraph Cody runs on web, windows, mac, linux.
Can I use Azure Machine Learning for free?
Yes. Azure Machine Learning has a free tier, so you can try it without paying. Sourcegraph Cody starts at $59/month.
What is Azure Machine Learning best used for?
Azure Machine Learning is most often used for enterprises standardised on azure where using a different cloud for machine learning would mean a fresh security and compliance review, training that needs to burst onto a gpu cluster occasionally without buying hardware, with the cluster scaling back to zero afterwards, regulated workloads that must stay inside a virtual network with private endpoints and auditable role-based access, teams already using mlflow who want the tracking interface they know backed by a managed service and enterprise identity. Of those, enterprises standardised on azure where using a different cloud for machine learning would mean a fresh security and compliance review and training that needs to burst onto a gpu cluster occasionally without buying hardware, with the cluster scaling back to zero afterwards are not what Sourcegraph Cody is typically brought in for.
What can Azure Machine Learning do that Sourcegraph Cody cannot?
Azure Machine Learning covers Workspace, Compute clusters, MLflow-compatible tracking, Model registry. Sourcegraph Cody covers Multi-repository context, Large context window, Context filters, Model flexibility.

Answered from the vendors’ own pages

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.

Sourcegraph Cody: Is Sourcegraph Cody still available to individual developers?

No, as of mid-2025 Cody Free and Pro plans were discontinued; Cody is now sold only as part of Sourcegraph's Enterprise plan, which requires an annual contract.

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.

Sourcegraph Cody: How much does Sourcegraph Enterprise cost?

Enterprise plans start around $16,000 and scale with team size and seat count, including bundled AI credits; exact pricing requires a sales quote.

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.

Sourcegraph Cody: How does the AI credit system work on Enterprise plans?

Each plan includes a pooled allocation of AI credits shared across the organization; credits do not expire and roll over at renewal, with volume credit add-ons available.

Source
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.

Sourcegraph Cody: What happens if my organization exceeds its credit allocation?

Sourcegraph's pricing page addresses overage and offers additional volume credit buckets for teams that need more than their committed allocation.

Source
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.

Sourcegraph Cody: Is a free trial available for Sourcegraph Enterprise?

Sourcegraph's pricing page lists free trial availability as one of its published FAQ topics for prospective Enterprise customers.

Source
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