SAS Vs R: Difference You Should Know | ACTE

SAS Vs R: Difference You Should Know

Last updated on 16th Jul 2020, Blog, General

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  • R programming is an open-source counterpart programming language for SAS. R is a low-level language closer to C++. It is more flexible and powerful, and it has more advanced graphical capabilities as compared to SAS.
  • However, learning R is difficult than mastering SAS. Let’s explore more on these two in this blog.
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A market leader in commercial analytics spaceAn effective data handling and storage facility
Provides a graphical point-and-click user interfaceA comprehensive and integrated collection of intermediate tools for data analysis
Data can be published in HTML, PDF, Excel, and other formats using the Output Delivery SystemOffers graphical facilities for data analysis and the display can be done in either soft or hard copy
Retrieves data from various sources and performs statistical analysisIncludes conditionals, loops, user-defined recursive functions, and input and output facilities

Features of SAS and R

1.Availability / Price

  • As I’ve already mentioned that SAS is commercial software, not an open source. It is one of the most expensive statistics software. Majority of professionals are not able to purchase SAS.
  • But the majority of large enterprises are using this software. That’s why it is holding the larger market share than R. In other word SAS is not for an individual rather than it is for the organisation.
  • On the other hand, R is an open source software. Therefore anyone can download it and use it by paying any charges. Price is a big concern between SAS vs R.

2. Ease of learning

  • SAS is easy to learn for anyone whether it is a professional or the beginner one. Basically, SAS works on PROC SQL which can be easily understood by the individuals who already understand the SQL.
  • Apart from that SAS also offers great UI to the users along with plenty of tutorials.
  • These tutorials are quite helpful in understanding the SAS software. In addition, it also offers that complete user manual whenever you purchase the software.
  • On the other hand, R is a tough programming language. It is quite tough for the beginner to use the R programming language.
  • It requires lots of efforts and dedication to master the R programming language. R is a low-level programming language thus it needs a write a longer code in it.

3. Progress in the application

  • R is an open source programming language, That’s why it always get the latest features faster than SAS. On the other hand, SAS provides the latest features in the new updates.
  • The development process of SAS is now becoming faster. On the other hand, R used by some of the professors in the past. The best part of SAS upgradation is that all its latest features analyzed in the managing environment.
  • On the other hand in R there are not well-analysed features comes when we get the latest update of R., In fact, R provides an open source community where the programmers and researchers do their contribution to make R better.

4. Statistical Capacity

  • Nowadays SAS programs and SAS stat pack a strong pack. In addition, it covers virtually the entire techniques and statistical evaluation. On the other hand, R is an open-source programming language.
  • Any individual can submit their program and contribute in developing the libraries of R. In this way, the most advanced cutting edge techniques always released in R.
  • With the help of individual efforts, CRAN is holding more than 15000 programs.
  • In addition, there are some of the most advanced techniques like GMLET, ADABoost RF can only be accessible with R. Other than that you can also obtain some experimental programs using R.
  • Some of the most powerful data miners also use R to construct their models.
  • On the other hand, SAS is paid software with technical support. SAS is used in several mission duties, where other techniques are unable to be premettired to creep in.
  • All the latest development and new statistical techniques are always checked before the release of the new software.

5. Customer care support & community:

  • R is known for its largest online community. R is an open source language that’s why there is no customer care support. If the user faces any problem with R then he/she can ask for the help in the R community.
  • On the other hand, SAS software provides dedicated customer care support along with the community. Whenever the user faces any problem with the SAS software, they can ask for help to technical support.
  • On the other hand, if they want to stay updated with the software features and new releases. Then they can ask the same in the community.
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Difference Between SAS and R

  • SAS vs R is the comparison between two industry-leading analytics tools or language.SAS known as Statistical Analysis System is an enterprise provides the tools for business analytics.
  • Whereas, R is an open source programming language that is widely used for statistical and data science. SAS provides several out of the box features and supports for analytics and is limited to large enterprises for its licensing constraints. Whereas R language supported by the growing community and advanced packages are build and contributed to the community for R program implementation.
  • SAS is efficient to process very high size datasets. Whereas, R is limited to the large size data processing as it processes the data.

The most popular and used tools for data analytics are SAS vs R.

  • SAS is largely initiated in big corporations because they have high customer service, that’s why they play a vital role in financial services and marketing companies.
  • SAS code is executed within its own SAS system, R code executes within the R’s statistical environment.
  • SAS has bit loops in data files record, in R loops are avoided.
  • R is used in mid-sized firms; telecoms companies require unstructured data for the data analysis and hence they use machine learning algorithms to work with for which R language is more suitable.
  • Ruses function like Decision trees, association rule, mining that is why they are used in the data mining process.
  • Significant disadvantages of R are they work only on RAM, whereas SAS works for increased data size.

Some of the R application are:

  • Largely used in the Finance process and market.
  • They help in data importing, cleaning.
  • Plays a vital role in data science as it gives a variety of statistics.

Where SAS can be applied and in which sectors?

  • Finance, Government, Healthcare domains, etc.
  • Predictive analytics
  • Business intelligence
  • Prescriptive analytics

Key Differences Between SAS and R

Both SAS vs R are popular choices in the market; let us discuss some of the major Difference Between SAS vs R.

  1. Easy to learn:
  • SAS is not difficult to learn they have complete instructions manual. As it’s a commercially licensed product there won’t be many levels of difficulty when it comes to coding where a user has to learn and build the code.
  • whereas R needs a Programming language to learn. They need to be implemented correctly or else leads to complex codes. The overall curve leads to average to high.

Customer Service:

  • SAS have good customer service; technical challenges are easily sorted has the largest online community but no customer support which makes much difficult for the user to tackle technical issues.
  • SAS is beneficial to end to end infrastructure with good quality.

Language dependent:

  • R is Object- Oriented and functional language, it is a highly extensive language. The source code for the R software is written in C and FORTRAN.
  • It is platform independent and supports all Operating System. SAS is based on SQL Language& is a procedural Language.


  • R has built-in library function and packages, so it is the best option for plot visualization. SAS provides components during installation in SAS system (ETS, database).
  • In SAS inputs are given in excel or from several data sources and the statistical analysis of the result is given in form of tables, graphs, HTML.


  • R has key advantages over statistical package is that sophisticated graphical abilities. R’s base graphics system allows us to have a fine control over essential plot and graph.

Data Security:

  • SAS – Security is highly maintained in SAS where huge MNCs rely on them to protect their data as there is a lot of predictive analytics being done.
  • When it comes to security, there is always a gap between the open source and the commercial product. Whereas Securities were not built well into R.
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SAS vs R Comparison Table

Below is the 6 topmost comparison between SAS Vs R

The basis of comparison                   SAS                         R 
Availability/Cost It is expensive, cost a lot of memory. It is not a free tool requires licensed software. It is a click and runs the software. R is Completely free and can be downloaded by anyone. They are low cost.
Graphical system They offer good GUI. an array of statistical function with technical support. They have highly advanced Graphical capabilities
Data Handling They handle large datasets (Terabytes of data) R has the largest drawback in handling Big dataset. R works on Ram, which makes difficult to run the small task.
Ease of use SAS is a commercial software. This tool has user-friendly GUI. It comes with documentation and tutorial base which can help learners to learn easily. Learning R is quite steep as we need to learn code at the root level.
Data science capabilities SAS are efficient are sequential data access. The drag and drop interface make it easy to create a statistical model. Statistical modes are written in few lines of code. R is mainly used when the task requires a standalone server.
Ranking  Ranked in 31st place in Jan 2012. Ranked in 24th place by TIOBE community.

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