Databricks vs SAS Visual Analytics comparison

The compared Databricks and SAS solutions aren't in the same category. Databricks is ranked #1 in Data Science Platforms , with an average rating of 8.2, and holds a 19.2% mindshare in the category. SAS is ranked #9 in DV , with an average rating of 8.5, and holds a 5.1% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 96% of SAS users who would recommend it.

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Executive Summary

We performed a comparison between Databricks and SAS Visual Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Knime, Amazon Web Services (AWS) and others in Data Science Platforms.

To learn more, read our detailed Data Science Platforms Report (Updated: December 2024).

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Data Science Platforms

December 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

Data Science Platforms

Data Visualization

Featured Reviews

Md Masudul Hassan

Agricultural Finance and IT Researcher at Sher-e-Bangla Agricultural University

Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts

I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.

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Dunstan Matekenya

Data Scientist at a financial services firm with 10,001+ employees

Process large-scale data sets and integrates with Apache Spark with notebook environment

Databricks integrates natively with Apache Spark, which I use as a processing engine for large-scale datasets. This native integration is one of its strengths. Another strength is that the platform makes it very easy to manage resources. For example, setting up a cluster of five or fifteen nodes is straightforward with Databricks. The notebook environment is also excellent, making it easy to perform various tasks.

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Robert Heck

Co Owner at Hecht und Heck GmbH

A great solution for big organizations, complex business requirements, and highly sophisticated and specialized statistics

There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else. For instance the system does not come with a pre-defined accounting, budgeting or planning model for a particular industry. Some competitors come with such a model (e.g. for retail companies) which makes the implementation of course easier if the customer can comproise with this predefined model. SAS does not provide such models but does not demand customers to comply with a foreign business model.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."

"You can quickly build models because it does the work for you."

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."

"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."

"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."

"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."

More IBM SPSS Statistics pros

"The initial setup phase of Databricks was good."

"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."

"The ease of use and its accessibility are valuable."

"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."

"The setup was straightforward."

"Databricks integrates well with other solutions."

"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."

"The integration with Python and the notebooks really helps."

More Databricks pros

"The technical support services are good."

"Simplifies report designs and quickly displays tables and graphs."

"The tool's most valuable features are its ease of use and advanced data visualization capabilities."

"The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps with quality assurance processes."

"It's relatively simple to create basic dashboards and reports."

"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."

"The speed to display charts and react to users' choices is great."

"It's quite easy to learn and to progress with SAS from an end-user perspective."

More SAS Visual Analytics pros

Cons

"It could allow adding color to data models to make them easier to interpret."

"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."

"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."

"It could provide even more in the way of automation as there are many opportunities."

"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."

"IBM SPSS Statistics does not keep you close to your data like KNIME."

"The technical support should be improved."

"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."

More IBM SPSS Statistics cons

"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."

"I believe that this product could be improved by becoming more user-friendly."

"CI/CD needs additional leverage and support."

"Doesn't provide a lot of credits or trial options."

"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."

"The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."

"I would like more integration with SQL for using data in different workspaces."

"I would like it if Databricks made it easier to set up a project."

More Databricks cons

"The licensing ends up being more expensive than other options."

"Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help."

"I haven't come across any missing features."

"The product is expensive and needs the integration of more languages."

"The integration aspects of the solution could be improved."

"The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy."

"Some capabilities are missing compared to Power BI, especially when working with spreadsheet types."

"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."

More SAS Visual Analytics cons

Pricing and Cost Advice

"It's quite expensive, but they do a special deal for universities."

"The price of IBM SPSS Statistics could improve."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

"More affordable training for new staff members."

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"I rate the tool's pricing a five out of ten."

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

More IBM SPSS Statistics pricing and cost advice

"It is an expensive tool. The licensing model is a pay-as-you-go one."

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"I would rate Databricks' pricing seven out of ten."

"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."

"Databricks' cost could be improved."

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."

More Databricks pricing and cost advice

"The product is expensive."

"SAS Visual Analytics is expensive, as is the rest of the platform."

"Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."

"Licensing is simple."

"The cost of the solution can be expensive. There is an additional cost for users."

"$10,000 per annum for an enterprise license."

"It's approximately $114,000 US dollars per year."

"It was licensed for corporate use, and its licensing was on a yearly basis."

More SAS Visual Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

University

Manufacturing Company

Financial Services Firm

16%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Financial Services Firm

20%

Government

13%

Computer Software Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Statistics?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

See all answers

What needs improvement with IBM SPSS Statistics?

IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...

See all answers

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or ...

See all answers

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designe...

See all answers

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analyti...

See all answers

What do you like most about SAS Visual Analytics?

The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced...

See all answers

What is your experience regarding pricing and costs for SAS Visual Analytics?

It's about an average of five. It's easy to scale, but it comes with cost.

See all answers

What needs improvement with SAS Visual Analytics?

Some capabilities are missing compared to Power BI, especially when working with spreadsheet types. Furthermore, Exce...

See all answers

Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 16% of the time

Alteryx vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 11% of the time

Amazon SageMaker vs IBM SPSS Statistics

Compared 6% of the time

More IBM SPSS Statistics Competitors

Dataiku vs Databricks

Compared 11% of the time

Informatica PowerCenter vs Databricks

Compared 8% of the time

Amazon SageMaker vs Databricks

Compared 8% of the time

Dremio vs Databricks

Compared 8% of the time

Looker vs Databricks

Compared 2% of the time

More Databricks Competitors

Tableau vs SAS Visual Analytics

Compared 25% of the time

Microsoft Power BI vs SAS Visual Analytics

Compared 21% of the time

Dataiku vs SAS Visual Analytics

Compared 5% of the time

Microsoft Azure Machine Learning Studio vs SAS Visual Analytics

Compared 4% of the time

SAS Enterprise Miner vs SAS Visual Analytics

Compared 3% of the time

More SAS Visual Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Databricks

December 2024

Download Databricks product report

Buyer's Guide

SAS Visual Analytics

November 2024

Download SAS Visual Analytics product report

Also Known As

SPSS Statistics

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

SAS BI

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IBM

Databricks

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SAS

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.

SAS Visual Analytics Features

SAS Visual Analytics has many valuable key features. Some of the most useful ones include:

Data
Interactive data discovery
Augmented analytics
Chat-enabled analytics
Sharing and collaboration
Visual analytics apps
Embedded insights
Location analytics
Security and administration
In-memory engine

SAS Visual Analytics Benefits

There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:

Machine learning and natural language: SAS Visual Analytics uses machine learning and natural language explanations to find, visualize, and narrate stories and insights that are easy to understand and explain. This enables you to find out why something happened, examine all options, and uncover opportunities hidden deep in your data.

Easy and efficient reporting: With SAS Visual Analytics, you can create interactive reports and dashboards so you can quickly summarize key performance metrics and share them via the web and mobile devices.

Easy to use: SAS Visual Analytics was designed to be easy to use. Its easy-to-use predictive analytics enables even business analysts to assess possible outcomes, which also helps organizations make smarter, data-driven decisions.

Self-service data: Self-service data preparation gives users the ability to import their own data, join tables, create calculated columns, apply data quality functions, and more. In turn, the solution empowers users to access, combine, clean, and prepare their own data in an agile way, which helps facilitate faster, broader adoption of analytics for your entire organization.

Reviews from Real Users

Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.

A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.

PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.

Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.

Buyer's Guide

Data Science Platforms

December 2024

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