Altair RapidMiner vs Databricks comparison

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Altair RapidMiner

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Executive SummaryUpdated on Jun 8, 2025

Databricks and Altair RapidMiner compete in the data processing and machine learning tools category. Databricks seems to have the upper hand in scalability and collaboration, while Altair RapidMiner excels in user-friendly no-code environments.

Features: Databricks offers strong scalability, integration capabilities, and supports multiple programming languages. It includes a comprehensive machine learning suite and high performance for big data processing. Altair RapidMiner is valued for its ease of use, intuitive interface, and powerful no-code environment, supporting various file formats and automation features that appeal to non-programmers.

Room for Improvement: Databricks could improve visualization tools, better integrate with reporting tools, and enhance error message clarity. Users note high pricing and require improved documentation. Altair RapidMiner could extend its machine learning algorithm support, enhance deep learning, and offer more affordable pricing. Usability issues and tool integration improvements are also desired.

Ease of Deployment and Customer Service: Databricks is widely used in cloud environments with strong customer support, though there are some concerns about responsiveness. Altair RapidMiner primarily offers on-premises deployment with comprehensive documentation, though technical support varies.

Pricing and ROI: Databricks has competitive pricing in cloud contexts but is expensive for resource-heavy tasks. However, it achieves positive ROI through reduced infrastructure costs. Altair RapidMiner's freemium model and free educational licenses make it accessible, but paid versions are costly, with positive ROI due to comprehensive features and competitive licensing fees.

To learn more, read our detailed Altair RapidMiner vs. Databricks Report (Updated: July 2025).

Altair RapidMiner vs. Databricks

July 2025

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Review summaries and opinions

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

Categories and Ranking

Altair RapidMiner

Ranking in Data Science Platforms

7th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Predictive Analytics (2nd)

Databricks

Ranking in Data Science Platforms

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (8th), Streaming Analytics (1st)

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.6%, up from 7.2% compared to the previous year. The mindshare of Databricks is 15.3%, down from 19.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Rathnam Makam

Senior Technical Manager at a computer software company with 1,001-5,000 employees

A no-code tool that helps to build machine learning models

One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users. I haven't explored the tool's latest version, so I'm unaware of the current features. However, I think it would be beneficial if they could enhance capabilities related to deep neural networks, provide better support for generating UI, and allow for importing and utilizing large language models.

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ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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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

"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."

"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."

"The best part of RapidMiner is efficiency."

"RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the data stored there. RapidMiner offers a wider range of operators than other tools like Dataiku, making it a better option for my needs."

"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."

"The data science, collaboration, and IDN are very, very strong."

"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."

"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."

More Altair RapidMiner pros

"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."

"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."

"The solution offers a free community version."

"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."

"The notebooks and the ability to share them with collaborators are valuable, as multiple developers can use a single cluster."

"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."

"I think Databricks is very good at facilitating AI and machine learning projects; they implement AI and machine learning models very well, and clients can run their models on Databricks."

"It's very simple to use Databricks Apache Spark."

More Databricks pros

Cons

"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."

"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."

"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."

"One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users."

"I would appreciate improvements in automation and customization options to further streamline processes."

"I think that they should make deep learning models easier."

"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."

"RapidMiner can improve deep learning by enhancing the features."

More Altair RapidMiner cons

"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."

"Databricks has a lack of debuggers, and it would be good to see more components."

"It would be very helpful if Databricks could integrate with platforms in addition to Azure."

"The integration features could be more interesting, more involved."

"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."

"Databricks' technical support takes a while to respond and could be improved."

"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."

"The product needs samples and templates to help invite users to see results and understand what the product can do."

More Databricks cons

Pricing and Cost Advice

"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

"I used an educational license for this solution, which is available free of charge."

"For the university, the cost of the solution is free for the students and teachers."

"Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year."

"I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately priced, not too high or too low. It's worth the investment."

"The solution is affordable."

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

"The price is okay. It's competitive."

"The pricing depends on the usage itself."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"Price-wise, I would rate Databricks a three out of five."

"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."

"I would rate the tool’s pricing an eight out of ten."

More Databricks pricing and cost advice

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Top Industries

By visitors reading reviews

University

11%

Computer Software Company

11%

Educational Organization

10%

Manufacturing Company

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about RapidMiner?

RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the dat...

What is your experience regarding pricing and costs for RapidMiner?

I started with a trial version. We are likely to purchase a license, which may offer additional features.

What needs improvement with RapidMiner?

Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning. It would be beneficial if the platform co...

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 Python. It offers many different cluster choices and excellent integration with ...

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 designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

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 analytics teams that have to interpret data to further the business goals of their orga...

KNIME Business Hub vs Altair RapidMiner

Comparisons

Compared 51% of the time

Dataiku vs Altair RapidMiner

Compared 15% of the time

Tableau Enterprise vs Altair RapidMiner

Compared 8% of the time

Alteryx vs Altair RapidMiner

Compared 7% of the time

DataRobot vs Altair RapidMiner

Compared 2% of the time

More Altair RapidMiner Competitors

Dataiku vs Databricks

Compared 10% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Tableau Enterprise vs Databricks

Compared 5% of the time

More Databricks Competitors

Product Reports

Download Altair RapidMiner product report

Altair RapidMiner

August 2025

Download Databricks product report

August 2025

Also Known As

No data available

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Overview

Altair RapidMiner is a leading platform for data science and machine learning, offering a user-friendly interface with powerful tools for predictive analytics. It supports integration with APIs, Python, and cloud services for streamlined workflow creation.

RapidMiner provides an efficient data science environment featuring drag-and-drop functionality, automation tools, and a wide array of algorithms, making it adaptable for novices and experts alike. Users benefit from easy data preparation and analysis alongside robust support from a vibrant community. Challenges include better onboarding and deep learning model accessibility, alongside calls for enhanced image processing and large language model integration.

What features make Altair RapidMiner stand out?

Data science tools: Facilitates machine learning and predictive analytics.
Code-optional GUI: Enables non-programmers to create workflows seamlessly.
Integration: Supports APIs, Python, and cloud services.
Drag-and-drop functionality: Simplifies workflow creation for users.
Algorithm variety: Offers diverse methods for data analysis.

What benefits and ROI should users consider when evaluating?

Efficiency: Saves time in data preparation and workflow automation.
Accessibility: Intuitive design aids beginners and experts.
Community: Access to extensions and collaborative resources.
Documentation: Comprehensive tutorials enhance learning.

Altair RapidMiner is extensively used in business and academia, facilitating tasks like predictive analytics, segmentation, and deployment. In education, it supports data science teaching and research, while in industries such as telecom, banking, and healthcare, it's used for data mining, decision trees, and market analysis.

Altair

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.

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

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