Best Alternatives to SAS Viya

Explore 4 top-rated alternatives to SAS Viya in the ai/ml platform category. Compare features, pricing, and find the perfect fit for your needs.

About SAS Viya

Cloud-native data and AI platform that connects data, builds and governs models, and operationalizes decisions for regulated and risk-sensitive industries.

Enterprise

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Top Recommended Alternatives

Databricks

Machine Learning Platform

Unified analytics platform that combines data engineering, data science, and machine learning in a collaborative workspace.

Key Strengths:

  • âś“Unified lakehouse architecture eliminates the need to maintain separate data lakes and data warehouses, reducing data duplication and infrastructure complexity
  • âś“Built on open-source technologies (Apache Spark, Delta Lake, MLflow) which reduces vendor lock-in and enables portability

DataRobot

AI Data

From

Free

Enterprise AI platform for automated machine learning, MLOps, and predictive analytics with enterprise-grade governance and deployment capabilities.

Key Strengths:

  • âś“Powerful AutoML engine that automatically benchmarks dozens of algorithms with hyperparameter tuning, feature engineering, and a model leaderboard, dramatically reducing time-to-first-model.
  • âś“Strong MLOps capabilities including drift monitoring, automated retraining, model registry, and production performance tracking across hosted and externally deployed models.

H2O.ai

AI Development

From

Free (Open Source)

Enterprise AI platform uniquely converging predictive machine learning and generative AI with autonomous agents, featuring air-gapped deployment, FedRAMP compliance, and the industry's only truly free enterprise AutoML through H2O-3 open source.

Key Strengths:

  • âś“Only enterprise platform converging predictive ML and generative AI, enabling autonomous agents that forecast and reason in unified workflows—competitors require separate platform integration
  • âś“Air-gapped deployment with FedRAMP compliance makes it viable for banking, government, defense, and healthcare where cloud AI services are prohibited by regulation

Azure Machine Learning

Machine Learning Platform

Microsoft's cloud-based machine learning platform that provides ML as a service for building, training, and deploying machine learning models at scale.

Key Strengths:

  • âś“Deep integration with the broader Microsoft ecosystem including Azure AD, Microsoft Fabric, Azure Databricks, and GitHub Copilot
  • âś“Enterprise-grade security and compliance with certifications such as HIPAA, SOC 2, ISO 27001, and FedRAMP, suitable for regulated industries

Quick Comparison

ToolStarting PriceBest ForAction

SAS Viya

Current Tool

EnterpriseBuilt-in model governance, bias detection, and explainability make it one of the few platforms suitable out-of-the-box for regulated industries like banking and insuranceView Details

Databricks

EnterpriseUnified lakehouse architecture eliminates the need to maintain separate data lakes and data warehouses, reducing data duplication and infrastructure complexityView Details

DataRobot

FreePowerful AutoML engine that automatically benchmarks dozens of algorithms with hyperparameter tuning, feature engineering, and a model leaderboard, dramatically reducing time-to-first-model.View Details

H2O.ai

Free (Open Source)Only enterprise platform converging predictive ML and generative AI, enabling autonomous agents that forecast and reason in unified workflows—competitors require separate platform integrationView Details

Azure Machine Learning

FreemiumDeep integration with the broader Microsoft ecosystem including Azure AD, Microsoft Fabric, Azure Databricks, and GitHub CopilotView Details

Why Consider SAS Viya Alternatives?

While SAS Viya is a popular choice in the ai/ml platform category, exploring alternatives can help you find a tool that better matches your specific needs, budget, or workflow preferences.

Common reasons to explore alternatives include:

  • Different pricing models or more affordable options
  • Specific features that SAS Viya may not offer
  • Better integration with your existing tools
  • Performance or user experience preferences
  • Regional availability or support requirements

Compare the tools above to find the best fit for your specific use case.

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