Azure Machine Learning vs Huawei ModelArts

Azure Machine Learning7.3Visit HMHuawei ModelArts6.2Visit

Higher score Azure Machine Learning #3 in Low-Code Machine Learning Platforms Software 7.3/10 Paid ✓ 0 of 2 features Visit Microsoft

vs

HM Huawei ModelArts #9 in Low-Code Machine Learning Platforms Software 6.2/10 Paid ✓ 0 of 2 features Visit ModelArts

• Azure Machine Learning fits best

  Azure-centric teams building and operating ML models

• Huawei ModelArts fits best

  Huawei Cloud users seeking visual ML lifecycle tools

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Side by side

Feature	Azure Machine Learning 7.3/10 Visit ↗	HMHuawei ModelArts 6.2/10 Visit ↗
At a glance
Editor score	7.3	6.2
Ranking	#3 in Low-Code Machine Learning Platforms Software	#9 in Low-Code Machine Learning Platforms Software
Best for	Azure-centric teams building and operating ML models	Huawei Cloud users seeking visual ML lifecycle tools
Pricing model	Paid	Paid
Starting price	Not published	Not published
Free plan	—	Not published
Free trial	—	—
Deployment	Cloud	Cloud
Platforms	Web	Web
Support	Docs	Tickets, Docs
Built for	Mid-market, Enterprise	Small business, Mid-market, Enterprise
Features Azure Machine Learning 0/2 · Huawei ModelArts 0/2
Automated ML	Not published	Not published
Visual workflows	Not published	Not published
Specs
Deployment targets	Not published	Not published
Supported model types	Not published	Not published
Data source connectors	Not published	Not published
Access platforms	Not published	Not published
Our review
Pros	Automated ML, evaluation workflows, and reusable training pipelines Supports batch scoring and real-time HTTPS model endpoints MLOps monitoring supports retraining and redeployment	Low-code workflows span data, training, evaluation, and deployment Tracks experiments, model versions, datasets, and training results Supports real-time, batch, and edge inference deployment
Cons	No free plan; compute and other Azure resources are billed separately Compute savings plans require a 1- or 3-year commitment Documented support channel is documentation	Deployment is cloud-only Compute costs vary by specification, node count, duration, and region Resource planning is required for dedicated pools, Lite Clusters, or Lite Servers
Our verdict	Azure Machine Learning is a cloud service for data scientists, ML professionals, and engineers managing the machine-learning lifecycle. It combines automated model training, forecasting and time-series inference, evaluation workflows,… Read the review →	Huawei ModelArts is Huawei Cloud’s cloud-based AI development platform for AI developers, data scientists, and organizations building or operating machine-learning or foundation-model applications. It covers data preparation, notebook… Read the review →

Strengths and trade-offs

• Azure Machine Learning — where it wins

  • Automated ML, evaluation workflows, and reusable training pipelines
  • Supports batch scoring and real-time HTTPS model endpoints
  • MLOps monitoring supports retraining and redeployment

  Where it doesn't

  • No free plan; compute and other Azure resources are billed separately
  • Compute savings plans require a 1- or 3-year commitment
  • Documented support channel is documentation

• Huawei ModelArts — where it wins

  • Low-code workflows span data, training, evaluation, and deployment
  • Tracks experiments, model versions, datasets, and training results
  • Supports real-time, batch, and edge inference deployment

  Where it doesn't

  • Deployment is cloud-only
  • Compute costs vary by specification, node count, duration, and region
  • Resource planning is required for dedicated pools, Lite Clusters, or Lite Servers

• Azure Machine Learning7.3/10 · Paid

  A full ML lifecycle service for teams building and operating models in Azure.

  Visit MicrosoftFull verdict →
• HMHuawei ModelArts6.2/10 · Paid

  A visual, cloud-based ML lifecycle platform for Huawei Cloud teams.

  Visit ModelArtsFull verdict →