SPSS vs SAS | Top 10 Points of Comparison For The Best

Most of us are not sure about the comparison between SPSS vs SAS. If you are also not sure about it then in this blog, we will compare going to compare them on the basis of some criteria.

Data is playing a crucial role in our life. Sending a text over the internet to sending huge files over the internet all involves data transmission. And the data also contains some valuable information. That is why data becomes one of the essential elements of every business. But having the raw data is not useful for any business or organization. But how can we get the decision from the data? 

We can do so with the help of statistics. Yes, statistics is the only way that can transform the raw data into useful insights. We use it to provide data trends and predictions. But if we do statistics analysis manually, then we will not get the best results easily.

To overcome this problem, there are two most potent statistics analysis software, i.e., SPSS and SAS. But wait, there is a difference between them and SPSS is software by IBM. On the other hand, SAS is a complete programming language.

Both of these software and programming languages provide complex statistics solutions. Let’s compare both SPSS vs SAS based on some criteria:-

History of SPSS

The full form of SPSS is a statistical package for social sciences. It is the product of IBM and is known as IBM SPSS. It was launched in 1968 at the University of Stanford. Later on, after eight years, SPSS Inc was founded. In 2009 IBM acquired SPSS. That is the reason it is known as IBM SPSS.

Introduction to SPSS

It is widely used by researchers, education researchers, marketing organizations, and data miners. It was the first-ever statistical programming language for the PC. It is one of the best programming languages to do reporting via tables and charts. As the name suggests, SPSS is specially designed for social science.

But nowadays, you can use it for business analytics, business intelligence, data management, and predictive analysis. SPSS offers copy and pastes functionality. So that you can easily operate by click interface, it is relatively easy to learn SPSS.

It also offers the best-in-class documentation that gives clarity on statistical procedures algorithms. Data processing can be slow in SPSS when you have a large amount of data. SPSS is widely used in universities. SPSS offers limited syntax and is also slow compared with other programming languages to adapt to new technology changes.

History of SAS

SAS stands for a statistical analysis system. It was developed in 1966 and released in 1976 at North Carolina State University. The initial development of SAS was to analyze the immense quality of agriculture data. But later on, it is widely used for business analytics, business intelligence, data management, and predictive analysis.

Introduction to SAS

SAS is quite tough to learn, but it offers drag and drops options. If you want to customize things in SAS, then you should have in-depth coding knowledge in SAS to customize it as per your needs. You can have full control over SAS all because of its command-line interface. If you are a skilled coder, you can also take advantage of its advanced editor for coding.

SAS offers faster data processing. You can process a large amount of data easily in SAS. It has inbuilt algorithms for data sorting and splitting. That is the reason it can easily handle large amounts of data. You get the yearly license with SAS which is quite costly. SAS uses the Proc SQL for coding.

If you have good command over SQL, you will find SAS one of the easiest programming languages. It is widely used in industries.

Which is better, SPSS or SAS?

It is hard to consider anyone better than the other. In terms of documentation, SPSS is quite better because it has clarity on algorithms used for the statistics process. Apart from that SPSS also has the best in class interface than SAS.

On the other hand, SAS struggles a lot in both of these areas. But SAS is offering blazingly fast data processing as compared with SPSS. But when you have a small amount of data then SPSS can do it in a fraction of time.

What are the disadvantages of SPSS?

Although there are lots of disadvantages of SPSS. But here we will talk about the major limitation of SPSS. It is not as powerful as processing large data sets. There are lots of fields where the researchers need to work with a huge amount of data.

Therefore they don’t choose SPSS to process huge amounts of data. For this, they go with SAS or any other statistics software. 

Interest Over Time

The blue graph indicates SPSS, and the red graph indicates SAS as we can see that people have more interest in SAS than SPSS over 12 months.

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Comparison Between SPSS vs SAS

Purpose and Usability

You need not have in-depth statistics knowledge to start with SPSS. It offers a simple and easy-to-use interface with drop-down options. It is widely used in most statistics activities, but the significant role of SPSS is in social science. 

On the other hand, SAS is one of the best statistical programming languages. It offers a large amount of high-quality production code for various purposes. The significant use of SAS is in the analytical space. SAS provides the best-in-class programming environment where you can code the high-end statistics calculation easily.

Data Processing

SPSS allows us to process 100 MB of data in a single time. It is quite useful to process small amounts of data in seconds. 

On the other hand, if you want to process huge amounts of data, SAS is the best option. It is designed to process a huge crunch of data in a short time. You also get the facility like data sorting, splicing, and searching the data. 

Learning Curve

It is quite easy to learn SPSS as compared with SAS. It offers one of the easiest interfaces in the world. Anyone can get a good command of SPSS with the help of a quick tutorial on SPSS. It offers the paste function that is used to create the syntax for steps to be executed in the user interface. 

On the other hand, SAS is based on the Proc SQL which requires immense knowledge of coding. If you have a good command over SQL, then you will find SQL quite easy to use. Otherwise, it can be a nightmare for those who don’t have an interest in coding. 


SPSS is widely used in reputed universities around the world. It has a clean and easy-to-use interface. It comes with complete documentation. You also get the click and play functionality with SPSS which makes it quite easy to code in SPSS using the paste button. Besides, you also get the best customer support with SPSS; if you find any issue using this software,

On the other hand, SAS is widely used in the industry. You get the drop-down interface in SAS. That makes it quite convenient to use. Apart from that, if you have good command over programming and SQL, then you can use SAS at its full potential. 


SPSS is quite costly as compared with SAS. It has different licenses for different purposes. Its syntax has limited functionality. Therefore it is not adopting the new changes in technologies.

On the other hand, SAS is also costly. There are still some options that are not available in its interface. Thus you need to write the code to create the option and customize SAS as per your requirements. 

Data management

Data management is one of the best features of SPSS. It is quite easy and efficient to manage data in SPSS. 

On the other hand, SAS is also good for data management. SAS also has an edge over IBM SPSS and it is superior to R. It sets a breaking point to the volumes that can deal with it.


Zones that require utility have a choice for SPSS. It gives different capacities that can be stuck into the interface to get quick and exact outcomes. Subsequently, SPSS has the most straightforward learning. SAS likewise follows this.

R has the steepest expectation to absorb information among all. In R, we perform factual demonstrating through programming. In this manner, it is basic to know about programming essentials and programming standards in R.


SPSS is not offering the best-in-class documentation. It has a lack of documentation as compared with SAS. On the other hand, SAS is offering the best-in-class documentation that includes everything about SAS programming.

Decision Tree

When it comes to decision trees, IBM SPSS has an edge over SAS. It has best-in-class support from the execution of choice tree calculations. 

On the other hand, if you want to execute a decision tree in SAS then you have to purchase the expensive information mining suite. It means that it will cost you a lot when it comes to executing a decision tree in SAS.

Key Features

The key feature of IBM SPSS is that it offers the best in class capabilities to set up and download its packages. It doesn’t require in-depth knowledge to learn SPSS because of its more accessible graphical user interface and the ability to run scripts with extensive coding knowledge. It also has built-in data scrubbing and staging capabilities.

On the other hand, SAS offers the best in class coding language i.e. SAS coding language. It is an extensive programming language that allows you to make SAs a more powerful programming language.

It is the perfect choice to manage and handle large amounts of data easily. Apart from that it also provides best-in-class support for its users whenever they require it. 


Although SPSS is offering best-in-class visualization and higher-quality graphics. But if you need to make the output presentation-ready then you need to export it to other programs. It is not well suitable with Mac products.

On the other hand, SAS requires more coding knowledge as compared with SAS to have the best command over it. Apart from that it also offers slow performance. But if the system is quite powerful then you can run SAS smoothly. Other than that SAS is not offering advanced analytics capabilities to Mac users.


We have seen the comparison between SPSS vs SAS. Both of this software are quite powerful in performing data analytics and data processing operations. If you have a small amount of data, you should go with SPSS because it processes that data within a few minutes.

But if you have a large set of data and you can wait for the processing, you should go with SAS. You can also pick on this software as per your coding knowledge. If you have a good command of coding, SAS is best for you.

Otherwise, you can go with SPSS. SPSS is widely used in the education sector, while SAS is widely used in the industry where a huge amount of data is processed daily. It is good to go with SAS if you want to have a good career in the data analytics industry. 

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