MATLAB vs SAS Viya

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Our analysts compared MATLAB vs SAS Viya based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

Product Basics

MATLAB is a numerical computing and programming platform that enables users to develop and implement mathematical algorithms, create models and analyze data. Designed for engineers and scientists, it can be used for a range of purposes, including deep learning and machine learning, computational finance, image processing, predictive maintenance, IoT analytics and more. Built around its matrix-based programming language, it can help users run analyses on large data sets as well as design and rigorously test models.

It is available through on-premise installation on Windows and Mac. For eligible licensees, there is also a SaaS version accessible through a web browser. Users can purchase it under a perpetual or annual license, with discounts for academic institutions. For individuals not associated with government agencies, private companies or other organizations, there is a less expensive home license for personal use. Students can purchase a student license for a version designed for coursework and academic research.

Early-stage technology startups can apply for startup-friendly pricing and opportunities.
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SAS Viya is a cloud-based in-memory analytics engine that provides data visualization, reporting and analytics to businesses for actionable data insights. Powered by AI, it brings together visual analytics, visual statistics and data science for enterprises to achieve end-to-end self-service analytics. It uses a standardized code base with support for programming in R, Python, SAS, Java and Lua.

Deployable in the cloud, on-premises and hybrid environments, it integrates with a wide range of business applications through an agile, scalable architecture. The vendor offers an introductory 30-day free trial.

Pros
  • Comprehensive features
  • Powerful analytics capabilities
  • User-friendly interface
  • Scalable architecture
  • Strong support from SAS
Cons
  • Steep learning curve
  • Limited customization options
  • High cost of ownership
  • Potential vendor lock-in
  • Resource-intensive
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$980 Annually
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Tailored to your specific needs
$10,000 Annual
Get a free price quote
Tailored to your specific needs
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Product Assistance

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Product Insights

  • Get Results Faster: Obtain quicker results through contextual hints, automatic code generation and a fully integrated debugger. Spend less time on programming and troubleshooting.
  • Analyze with Less Code: Teach the platform to automatically generate code to reproduce work and save time, as well as perform tasks such as training machine learning models or labeling data. 
  • Add-Ons For Every Application: Customize and extend the functionality of the core platform through the MATLAB family of add-on products to address specific business needs.
  • Scale Up to Big Data: Scale analyses to process big data by running on clusters, GPUs and clouds. Speed up computation on large data sets without needing to rewrite code or learn big data programming. 
  • Updates and Upgrades: Runs code more than twice as fast as before, due to continual updates and new features on the platform, as well as twice-yearly new releases.
  • Access Anywhere: Sign in to the online platform from any standard web browser, without needing to download and install the application on new machines. Syncs files between computers and the online platform via cloud storage and integration, eliminating the need for manual upload or download. 
  • Enhanced Collaboration: Collaborate by sharing scripts and files directly online or publishing to the web via interactive controls. Easily package or translate analysis for other platforms, or document work and export it to reports for sharing.
  • Free Trial: Try it hands-on with a free 30-day trial. Students whose schools have a campus license can access a free copy of the software without the 30-day trial limitation.
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  • Improve Decision-Making: Make informed business decisions by using historical and current proprietary information to derive analytical insights. Compute vast amounts of data faster and resolve complexities through parallel processing. Boost workflow efficiencies by deploying operational decisions that define real-time best actions at scale. 
  • Self-Service Analytics: Easily perform automated forecasting, goal-seeking and scenario analysis — no technical skills needed. Identify user sentiment through text analytics and incorporate geographical data for a complete picture of business metrics. 
  • Maximize ROI: Save time through built-in automation for data prep, feature engineering, algorithm selection and AI-powered data discovery. Innovate, rather than spending time on tedious data management and analytics tasks. 
  • Data Security: Ensure data encryption at rest and while moving across systems, in addition to auditing protocols. Connect to external data management systems like Oracle, Teradata, Facebook, Amazon and Esri seamlessly through Kerberos, SAML, OAuth and OpenID. 
  • Data Management: Import data by using an IDE or through REST APIs, and visualize and analyze it through self-service data prep. Join tables, apply functions and perform calculations, or drag-and-drop, pivot, and slice and dice to view desired metrics. 
  • Augmented Analytics: Identify relationships in data through automatically generated suggestions and guided analysis, and track anomalies and outliers. Tell data stories by generating easy-to-understand visuals and dashboard summaries in natural language. Derive meaningful insights for the future by creating what-if scenarios for forecasting and predictive analytics. 
  • Mobility: Access business reports on the go through a native mobile app that supports a variety of charts, graphs and tables. Configure app functionality per device for specific users to add and view reports, share links, add and view comments and view alerts. 
  • Scalable Architecture: Leverage its modular microservices architecture to scale as per business needs. Monitor and manage the health and configuration of individual microservices instances through the SAS Environment Manager. Deploys seamlessly to any type of environment, including the cloud, and runs on Cloud Foundry as a platform-as-a-service (PaaS). 
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  • Data Import: Import and access a variety of data types, including text files, spreadsheets, images, audio, video, scientific data formats, IoT data, large data sets and more. 
  • Algorithm Development: Develop algorithms with thousands of core mathematical, engineering and scientific functions and tools for debugging, implementation and optimization. 
  • Automate with Machine Learning: Leverage interactive apps to see how algorithms work with data and then tweak to get the desired results. Then, automatically generate a program to reproduce or automate workflows. 
  • Live Editor: Build functions and generate code, creating scripts that can be enhanced with formatting through an interactive editor. Compile these scripts and results into an executable notebook. Explore parameters and immediately see the results, saving time.
  • Data Analysis: Analyze large data sets and big data in a multitude of ways through thousands of prebuilt functions for statistical analysis, machine learning and signal processing.
  • Data Visualization: Turn data into graphics with prebuilt 2D and 3D plots, including line plots, histograms, bar graphs, scatter plots, pie charts, word clouds, maps, polar plots, vector fields and animations.
  • Mathematics: Perform mathematical calculations via a vast library of mathematical functions, including linear algebra, statistics, Fourier analysis, numerical integration, differential equations and more.
  • Modeling: Supports model-based design, multi-domain simulation and automatic code generation via integration with another product from the same vendor, Simulink. Helps in numeric and symbolic modeling and provides mathematical tools like curve fitting, statistics, ODE and PDE solving, calculus and more.
  • Teach with Live Scripts: Build live scripts with its code to let students explore concepts and learn on their own. Create engaging lectures that walk students through explanations, math equations and results, one section at a time. Modify code on the fly to demonstrate how to use math to solve complex problems.
  • App Designer: Create, package and share professional desktop and web apps without needing all the technical know-how of app development. Lay out a graphical user interface through drag-and-drop tools and write the coding for the app’s behavior with an integrated editor and code analyzer that warns about errors in code as it’s written.
  • Community Gallery: See examples from the community on how to display and manipulate data by visiting the plot gallery and live script gallery on the vendor’s website.
  • Programming Integrations: Supports interfacing with other programming languages. Use the platform from within another programming environment without starting a new desktop session through engine APIs that support C/C++, Fortran, Java, Python and more. Call functions and objects from other libraries, including C, C++, Java, Python, .NET, COM objects and more from within the platform. Convert algorithms written in its code to C/C++.
  • Add-Ons: Utilize toolboxes and specialized solutions for fields such as math and optimizations, statistics and data science, code generation, application deployment, database access and reporting. These toolboxes are professionally built, rigorously tested and fully documented. Integrate automated reporting into the platform with richly-formatted custom reports in PDF, Word and HTML formats. 
  • MATLAB Online: Access the platform from any web browser through cloud-based services without downloading and installing the software. 
  • MATLAB Drive: Store, manage and share files from the cloud across devices and work with files from anywhere.
  • Mobile App: Learn and teach through mobile apps for iOS and Android devices. Connect to sessions, and acquire sensor data to analyze and capture images and videos.
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  • Visualization and Reporting: Dig into data for in-depth analysis and view key business metrics through autonomous data exploration and manipulation. Create and customize interactive reports and charts to share with others across the organization for collaborative insight. Get suggestions on graphics best suited to display pertinent data through auto charting. 
  • Data Modeling: Analyze data with predictive models through regression, clustering and neural networks. Ensure version control by tracking data models from creation through usage by registering, validating and monitoring each version. Creates snapshots of model properties and files and retains them for the future. 
  • Visual Statistics: Build diverse scenarios simultaneously and refine them with what-if analyses to uncover insights through experimentation. Unifies all business tools, irrespective of the language they support, into a common visual analytics solution. 
  • Cloud Integrations: Develop low-code technologies by porting SAS open-source models into mobile and business applications through its cloud-native capability. Optimize analytics workloads on clouds like Microsoft Azure and ensure cost-efficient migration of analytics to the cloud through a workload management tool. 
  • ML-Based Insights: Get valuable insights from new data types by combining structured and unstructured data in integrated machine learning programs. Choose the desired ML algorithm from a range of options and easily find the optimal parameter settings. Use Python within Jupyter notebooks for deep learning functions like computer vision, natural language processing, forecasting and speech processing. 
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Product Ranking

#11

among all
Big Data Analytics Tools

#41

among all
Big Data Analytics Tools

Find out who the leaders are

Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

MATLAB
SAS Viya
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Augmented Analytics Computer Vision And Internet Of Things (IoT) Dashboarding And Data Visualization Data Management Data Preparation Geospatial Visualizations And Analysis Machine Learning Mobile Capabilities Platform Capabilities Reporting 96 100 98 96 86 93 70 96 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

Excellent User Sentiment 4535 reviews
Great User Sentiment 203 reviews
92%
of users recommend this product

MATLAB has a 'excellent' User Satisfaction Rating of 92% when considering 4535 user reviews from 5 recognized software review sites.

85%
of users recommend this product

SAS Viya has a 'great' User Satisfaction Rating of 85% when considering 203 user reviews from 3 recognized software review sites.

4.5 (599)
4.2 (157)
4.6 (1808)
n/a
4.6 (1570)
4.3 (33)
4.6 (401)
4.7 (13)
4.3 (157)
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Awards

MATLAB stands above the rest by achieving an ‘Excellent’ rating as a User Favorite.

User Favorite Award

SelectHub research analysts have evaluated SAS Viya and concluded it deserves the award for the Best Overall Big Data Analytics Tools available today and earns best-in-class honors for Augmented Analytics and Computer Vision and Internet of Things (IoT).

Analysts' Pick Award
Augmented Analytics Award
Computer Vision and Internet of Things (IoT) Award

Synopsis of User Ratings and Reviews

Service and Support: All users who mentioned support said that online community forums are supportive in helping them leverage the platform to its maximum potential.
Data Processing: Around 92% of users who discussed its data processing capabilities said that the solution helps to simulate and visualize complex mathematical models in an intuitive manner.
Data Analysis: According to 92% of users who reviewed data analysis, the platform, with multiple built-in packages, is useful in exploring data, creating machine learning models and predictive analysis.
Functionality: Citing a range of pre-loaded functions and algorithms, approximately 88% of users who reviewed functionality said that the solution is a powerful tool with a rich feature set and strong computing abilities.
Ease of Use: Reviewing ease of using the tool, approximately 60% of users said that, with detailed documentation being readily available, minimal coding experience is necessary to create and combine scripts.
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Ease of Use: All users who mention its interface say that it makes autonomous analysis and data modeling accessible to users of all skill levels.
Support: All users who review support say that representatives are responsive and helpful in resolving issues and queries.
Functionality: Around 71% of the users who comment on its feature set say that the software helps discover data insights through powerful visualizations and on-the-fly calculations.
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Performance and Speed: Around 91% of users who reviewed speed said that the platform is resource-hungry in terms of power and space and slows down when performing complex computations.
Cost: Citing licensing costs, approximately 81% of users said that the software is expensive for individual users.
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Cost: All users who discuss its pricing say that the cost of acquisition is high.
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MATLAB is a computing and programming tool that combines the power of functions and algorithms with data integration, modeling and visualization for predictive business data analysis. Users perform complex computations on data sets that the platform ingests from a multitude of data sources to glean business-specific metrics. Citing online communities, all users who reviewed support said that the tool is accessible to beginners, while providing enough depth for advanced users, though some said that the coding syntax could be daunting for non-technical users initially. Around 92% of users who reviewed its analytical capabilities said that the platform provides a wide range of built-in packages to provide out-of-the-box data analysis solutions. With its minimal scripting, many users who discussed data processing said that they could simulate complex mathematical functions to visualize complex data models. Reviewing its functionality, many users said that its rich library and design makes it possible to write powerful programs easily. A majority of users who discussed its performance said that the platform consumes a lot of power and space and slows down when performing complex computations, possibly because updates, though frequent, do not include optimization for older features. Many users who reviewed the cost said that individual user licenses are expensive, and buying additional libraries adds to the cost since many of these have interlinking dependencies, though some users said that the platform provides value for money. In summary, MATLAB is a programming solution that leverages machine learning for data collection and complex computations for users to create data models and visualize enterprise metrics for predictive analysis.

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SAS Viya is an AI-powered data management and visual analytics platform with a robust, scalable architecture. All users who reviewed data source connectivity said that it connects to multiple sources and integrates easily with business applications, giving a seamless user experience. With fast in-memory processing of big data sets, it leverages the power of R to enable visual statistics. All users who mentioned predictive analysis said that it enables automated forecasting through what-if scenarios, goal-seeking, text mining and decision trees. Citing ease of use, all users say that the platform is intuitive and enables easy data modeling and self-service visual analytics. All users who mentioned support said that they are responsive and knowledgeable. Around 71% of the users who comment on its functionality say that it is a robust, scalable and flexible platform that enables visualization and analysis of business data, though some users say visual statistics need improvement. On the flip side, all users who review its cost say that the tool is expensive. In summary, SAS Viya is an analytics tool that provides data management, visualization and AI-powered analytics to enterprises for improved decision making, though small organizations and startups might find it cost-prohibitive.

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