SPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).
$99
per month per user
Microsoft SQL Server
Score 8.7 out of 10
N/A
Microsoft SQL Server is a relational database.
$1,418
Per License
Pricing
IBM SPSS Statistics
Microsoft SQL Server
Editions & Modules
Base
USD 3,830
one-time fee per user
Standard
USD 8,440
one-time fee per user
Professional
USD 16,900
one-time fee per user
Premium
USD 25,200
one-time fee per user
Monthly subscription
USD 99
per month per user
Annual subscription
USD 1,188.00
per year per user
Subscription
$1,418.00
Per License
Enterprise
$13,748.00
Per License
Offerings
Pricing Offerings
IBM SPSS Statistics
Microsoft SQL Server
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
IBM SPSS Statistics
Microsoft SQL Server
Considered Both Products
IBM SPSS Statistics
Verified User
Anonymous
Chose IBM SPSS Statistics
Advanced statistical analysis is possible which is not possible in powerbi. It is very much easy to prepare basic charts. I dept statistical tests like regression analysis can be done. It is user -friendly and even layman can understand basic data easily through IBM SPSS's …
Data Scientist ,Pre-Sales,Consultor/Instrutor em Estatística e Mineração de dados em Big Data
Chose IBM SPSS Statistics
I also point out that the two softwares are complementary, then IBM SPSS Statistics works very well with statistical tests, creation and visualization of detailed tables and creation of statistical project models and project models. The IBM SPSS Modeler helps you quickly view …
Occupational Safety, Health, and Environment Technician
Chose IBM SPSS Statistics
I have also used other statistical software such as the SAP Predictive Analytics software, SAP possesses most of the decode options as SPS, but it is not as graphical and easier to use as SPS. Thus, IBM SPSS Statistics was chosen as a primary and powerful statistical tool that …
We had not ever used anything as diverse as IBM SPSS Statistics before, so don't have much to compare it to but would highly recommend it based on all the previous comments before here. The platform is easy to use and again gives you a quick snapshot of company health based on …
If you have made it this far, you should have a very good idea of how SPSS stacks up the competition (data processing and analytics tools). Even the free ones, such as r Studio or Stata, are leaps and bounds ahead of SPSS. IBM is resting on a reputation developed nearly 30 …
We used IBM SPSS Statistics as it works well with the other IBM tools that we use. It may not work as well for smaller organizations with limited budget/resources. We have a mix of technical and devops people and this tool is easily used by everyone on the team globally.
I have on many occasions launched new versions of a big Python application in production, only to immediately drown in errors, caused by exceptions that were in turn caused by Python code where a single glance confirmed that it could never ever work and consequently had never …
IBM SPSS Statistics is much easier to use, even in classes with students, compared to other similar data analytic software that I have used previously. I selected it because of this reason and I plan to continue using it in the future. The interface is user friendly and the …
I, along with my supervised research student, used IBM SPSS Statistics compared to other software because of its simplicity and user-friendliness. A timeframe is a fundamental part of research work. Time is precious for both of us in terms of research work and using IBM SPSS …
The price of IBM SPSS and its quality-price ratio was one of the triggers for choosing the software over the competition. The ease of obtaining a demo of the product and the continuous training it presents was another of the key points in the decision making we made in the …
Its better for quick tasks, Psychology, Sociology, may lack in complex models, AI, or business-decision-making models. It's better for things that you want to compare, correlate or detect influence of one on the other. It's worse that R for complex models, custom models, big …
I also use or have used Tableau, Excel, and R (wasn’t able to list R above). Tableau is better for visualizations, Excel works for generalized/more basic statistical analysis but lacks more complex features, and R has been difficult for me to master and lacks the UI and ease of …
Compared to stata, python and MPlus, SPSS is more user friendly especially for beginners. It displays data and output in easily readable formats and makes statistics fun and easy. However, stata, python and MPlus are more ideal for complex statistical methods like structural …
IBM SPSS Statistics Logistic Regression's user-friendly interface is among its most important benefits. Without the need for sophisticated technical knowledge, users can navigate and analyze their data with ease. As a faculty member of a university, I used it using its numerous …
For my own statistical analyses, I personally use R and MPlus. However, these tools have a steep learning curve and require dedicated time and a course on their own. In m yopinion, they are not useful for trying to quickly acclimate undergrads to the new world of stats and …
We tend to shy away from open source where possible. with SPSS from our feeder university system for our co-op interns, this is a great transition and a low barrier to getting them working quickly.
IBM SPSS Statistics beats the pants off of Minitab in every area except cost. Minitab has far cheaper entry-level costs, but the software is much more limited. With the versions of Minitab I have used, importing mapping data is a non-starter. With IBM SPSS Statistics, once the …
I described this in a previous question. R is free and full of features, but time consuming to learn, especially since you have to download different libraries for whatever you're doing. I know IBM SPSS Statistics fairly well, and it has been worth the cost, but maybe not for …
You could consider i did use Mysql since i worked with some websites that were using a mysql database. I could not give a side by side comparision since i don't use those like i use the Microsoft SQL , but so far it worked well. I prefer Microsoft SQL due to support and info …
UI of the Microsoft SQL Server makes it easy to use and learn. The better technical support and documentation give it an extra edge over other databases. The Microsoft ecosystem provides additional advantages, as we can seamlessly use other Microsoft products, such as Power …
Microsoft SQL Server is faster and more compatible, but it does cost more, so you're paying for those features. I use the others in many other places where critical transaction processing time and compatibility aren't of great concern.
Microsoft SQL is slower than MySQL and Access but far more feature-rich and reliable. Access is almost obsolete nowadays, so not too many people are considering it, but unless budget or an open-source ethos is a factor, Microsoft SQL is superior in every way. Many commonly used …
The first database application taught when I was in school was Microsoft SQL Server. Microsoft SQL Server was used where I first started, so I had the opportunity to improve myself in MySQL. SQL is also used in my current workplace. It is widely used in very large projects due …
We have a few different DB's in the organization, including: Pervasive, Oracle, Db2, MySQL. Many of them are of limited use for one specific application. These don't really compare to MS SQL server. Oracle is heavy and cumbersome and overkill for smaller apps. Pervasive - …
Microsoft SQL Server is a comprehensive solution as transactional database, data warehouse, analytics, reporting, and ETL. It also integrates with the cloud well (Azure). The ease of use and setup makes this better than Oracle Database because the query syntax is also different …
I think both tools are really powerful and close to each other but since I moved to Europe I realized that most of the companies have been using SQL Server which in my opinion means something. The support from Microsoft I also consider a bit better and you can also find more …
Microsoft was the original creator of the SQL database, and thus, they still rule the market and drive innovation when it comes to data warehousing systems. It's comparable in price and allows you to retain the structured datasets that you lose when you change to a NoSQL …
[Microsoft] SQL Server has a much better community and professional support and is overall just a more reliable system with Microsoft behind it. I've used MySQL in the past and SQL Server has just become more comfortable for me and is my go to RDBMS.
Microsoft SQL Server and Oracle are both extremely powerful and scalable enterprise relational database platforms. Microsoft SQL sets itself apart with its ease of use and licensing and support model. Microsoft is good company to work with and they provide clear and …
It just boils down to why learn anther product when you are going to run across it so seldom. Developers determine what database engine I am going to need so I just tend to pick products for implementation that use a well know product that has lots of support resources …
The most known and widely used competitor of Microsoft SQL is most probably the open-source MySQL. If given the choice I would personally choose MySQL over Microsoft's SQL Server, mainly because it is totally free and open source, but also because it integrates better with …
[Microsoft SQL Server] offers a full solution, Inhouse Applications and hosted application continue to use SQL as backend database. Allows easy creation of development environments and continuous feature release.
All of the platforms have their own benefit. I was not the decision maker in selecting Microsoft SQL Server, as it was already being utilized when I joined the company, 7 years ago. I can say that I feel more comfortable with utilizing this platform as opposed to the other ones.
The free version is very powerfull and easy to install and use for small companies. Going to Professional and Standard, gives you all the support and the flexibility needed. It is known within the Database Administrator crew, and you can get support very easily over the …
Native to Windows and being required for other MS apps puts it above others in terms of usage. If we were not heavily dependent on Microsoft applications or OS, we might have considered other database solutions. It's an expensive solutions but it is a solid reliable solution. …
I was not too impressed with Oracle. Following the manual prohibited installation. They did provide a phone number and explained the manual was wrong and provided me with the correct information with which I was able to install the product. This was awhile back and I do not …
Microsoft SQL Server is one of the fastest RDBMS systems available in the market. Pricing is a bit on the higher side but all the features it provides pretty much justifies it. It can be integrated with a large number of frameworks thus enabling to work on multiple frameworks …
Microsoft SQL Server is still the industry standard for the type of development we do, and the types of applications that we use. Almost every developer or analyst we hire has at least a reasonable grounding in the use of SQL servers, and it is almost universally compatible …
We stopped looking at alternatives to Microsoft SQL Server a long time ago simply because it meant only having one DBMS that we needed to learn and to support. If we were to implement other database solutions that don't run on SQL Server, we would have to spend more time moving …
SPSS is well-suited for the following: 1) User Behavior Analysis: SPSS handles large datasets to analyze user behavior data. 2) Customer Satisfaction / Foundational Surveys: SPSS facilitates analysis of quant data from satisfaction surveys, keeping us informed about customer needs and preferences. 3) A/B test analysis: SPSS statistical tools for A/B test analysis, which helps optimize user experience of our products. Scenarios where SPSS are less appropriate: 1) Qualitative Data Analysis: I do not use SPSS for open-ended survey responses/qual data. 2) Live/in-vivo data analysis: SPSS is not ideal for real-time data processing. 3) Complex Data Integration: SPSS isn’t the best fit for complex data integration tasks
Microsoft SQL Server is ideal for highly available SQL workloads by using SQL Server Always On availability groups. Microsoft SQL Server might not be appropriate for solutions which require a very low resource footprint, since it requires significant CPU cores and RAM memory as well as high IOPS, always depending on the usage scenario.
SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.
It's super easy to use for newbies and super powerful for power users! It does EVERYTHING you are usually asked to do analytically. Their Help Desk is PHENOMENAL. And I find the upgrade and renewal price to be a good deal.
I think it is unlikely that sql server has disappointed someone, it is likely that someone will come initially discouraged if the needs and problems that occur are very challenging, but definitely have a SQL oriented system means having a solid base to work and on which maintain the their data securely
SPSS is beginner friendly and user-friendly for beginner analysts and simple statistical tests. It's "click and go" interface does take some learning, but overall this is much easier than other programs I have used and seen. Compared to SAS software, SPSS takes a great deal less familiarizing and it not a matter of learning a coding language like SAS and RStudio.
SQL Server mostly 'just works' or generates error messages to help you sort out the trouble. You can usually count on the product to get the job done and keep an eye on your potential mistakes. Interaction with other Microsoft products makes operating as a Windows user pretty straight forward. Digging through the multitude of dialogs and wizards can be a pain, but the answer is usually there somewhere.
I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end
We managed to handle most of our problems by looking into Microsoft's official documentation that has everything explained and almost every function has an example that illustrates in detail how a particular functionality works. Just like PowerShell has the ability to show you an example of how some cmdlet works, that is the case also here, and in my opinion, it is a very good practice and I like it.
Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.
Other than SQL taking quite a bit of time to actually install there are no problems with installation. Even on hardware that has good performance SQL can still take close to an hour to install a typical server with management and reporting services.
If you have made it this far, you should have a very good idea of how SPSS stacks up the competition (data processing and analytics tools). Even the free ones, such as r Studio or Stata, are leaps and bounds ahead of SPSS. IBM is resting on a reputation developed nearly 30 years ago and has shown no desire to improve.
Microsoft SQL is slower than MySQL and Access but far more feature-rich and reliable. Access is almost obsolete nowadays, so not too many people are considering it, but unless budget or an open-source ethos is a factor, Microsoft SQL is superior in every way. Many commonly used tools, like Crystal Reports, support it.
I found SPSS easier to use than SAS as it's more intuitive to me.
The learning curve to use SPSS is less compared to SAS.
I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.
Increased accuracy - We went from multiple users having different versions of an Excel spreadsheet to a single source of truth for our reporting.
Increased Efficiency - We can now generate reports at any time from a single source rather than multiple users spending their time collating data and generating reports.
Improved Security - Enterprise level security on a dedicated server rather than financial files on multiple laptop hard drives.