BigML vs SAS Viya Comparison: Reviews, Features, Pricing & Alternatives in 2026

Detailed side-by-side comparison to help you choose the right solution for your team

Updated Apr 2026 8 min read

BigML

0.0 (0 reviews)

BigML is a comprehensive machine learning platform that provides a programmable, scalable, and automated environment for building and deploying predictive models across various business applications and industries.

Starting at Free
Free Trial NO FREE TRIAL
VS

SAS Viya

0.0 (0 reviews)

SAS Viya is a cloud-native data management and analytics platform that helps you build, deploy, and manage artificial intelligence and machine learning models to solve complex business problems efficiently.

Starting at --
Free Trial 14 days

Quick Comparison

Feature BigML SAS Viya
Website bigml.com sas.com
Pricing Model Freemium Custom
Starting Price Free Custom Pricing
FREE Trial ✘ No free trial ✓ 14 days free trial
Free Plan ✓ Has free plan ✘ No free plan
Product Demo ✓ Request demo here ✓ Request demo here
Deployment cloud saas on-premise mobile
Integrations Zapier Google Sheets Amazon S3 Microsoft Azure Google Cloud Storage Node.js Python Ruby Java Swift Microsoft Azure Amazon Web Services Google Cloud Platform Python R Jupyter Snowflake Databricks Microsoft Teams Slack
Target Users small-business mid-market enterprise mid-market enterprise
Target Industries finance healthcare government
Customer Count 0 0
Founded Year 2011 1976
Headquarters Corvallis, USA Cary, USA

Overview

B

BigML

BigML provides you with a unified platform to build, share, and operationalize machine learning models without needing a PhD in data science. You can import your data and immediately start generating insights through an intuitive interface that handles everything from data preprocessing to model deployment. Whether you are working on classification, regression, or cluster analysis, the platform automates the heavy lifting of algorithm selection and parameter tuning.

You can integrate predictive capabilities directly into your applications using their extensive API or execute complex workflows with their domain-specific language, WhizzML. The platform is designed to scale with your needs, supporting everything from small experimental datasets to massive enterprise-grade data processing. It solves the common problem of the 'last mile' in machine learning by making it easy to turn a trained model into a live, functional web service.

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SAS Viya

SAS Viya is a cloud-native analytics platform designed to help you manage the entire data lifecycle in one place. You can move from raw data to production-ready AI models using a unified interface that supports both visual drag-and-drop tools and popular programming languages like Python and R. This flexibility allows your data scientists and business analysts to collaborate effectively on the same projects.

The platform handles massive datasets with ease thanks to its distributed, in-memory processing engine. You can deploy it on any cloud provider or on-premises environment to maintain control over your infrastructure. By automating repetitive data preparation and model tuning tasks, you can focus on uncovering insights that drive better business decisions and operational efficiency across your entire organization.

Overview

B

BigML Features

  • Automated Machine Learning Find the best performing models automatically with OptiML, which iterates through various algorithms and parameters for you.
  • WhizzML Automation Automate complex machine learning workflows and create repeatable processes using a dedicated domain-specific language.
  • Visual Model Interpretation Understand your data better with interactive visualizations of decision trees, ensembles, and clusters that reveal hidden patterns.
  • Real-time Predictions Turn your models into immediate web services to generate instant predictions for your web or mobile applications.
  • Image Processing Expand your capabilities by training models on image data for visual recognition and classification tasks directly.
  • Time Series Forecasting Predict future trends and seasonal patterns in your data with specialized tools for temporal data analysis.
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SAS Viya Features

  • Visual Data Preparation. Clean and transform your data using an intuitive visual interface that automatically generates code in the background.
  • Automated Machine Learning. Build high-quality models faster by letting the system automatically handle feature engineering, algorithm selection, and hyperparameter tuning.
  • Model Management. Register, track, and monitor all your analytical models in a central repository to ensure they perform reliably over time.
  • Open Language Support. Write code in Python, R, or Lua while still taking advantage of the platform's powerful distributed processing capabilities.
  • Real-Time Decisioning. Embed your analytical models directly into business processes to trigger automated actions and responses the moment data arrives.
  • Natural Language Generation. Receive automated text explanations of your data visualizations so you can understand the 'why' behind your business trends.

Pricing Comparison

B

BigML Pricing

FREE
$0
  • Up to 16MB per task
  • 2 concurrent tasks
  • Unlimited datasets
  • Unlimited models
  • Access to BigML Gallery
S

SAS Viya Pricing

Pros & Cons

M

BigML

Pros

  • Intuitive web interface simplifies complex data science tasks
  • Excellent documentation and educational resources for beginners
  • Powerful API makes integration into existing apps easy
  • Visualizations help explain model logic to stakeholders
  • Flexible pricing allows for low-cost experimentation

Cons

  • Interface can feel dated compared to newer tools
  • Advanced users may find visual tools slightly limiting
  • Large dataset processing can become expensive quickly
A

SAS Viya

Pros

  • Handles extremely large datasets with high performance
  • Unified environment for both coding and visual users
  • Strong governance features for regulated industries
  • Excellent technical support and extensive documentation
  • Seamless integration with major cloud providers

Cons

  • Higher price point compared to open-source alternatives
  • Significant learning curve for the full feature set
  • Initial setup and configuration can be complex
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