Altair RapidMiner vs Databricks comparison

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Altair RapidMiner

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Executive SummaryUpdated on Sep 14, 2025

In the realm of data analytics platforms, Databricks and Altair RapidMiner both offer robust solutions, yet they cater to different audiences. Databricks holds an advantage with enterprise users seeking scalability and advanced data processing capabilities via its Spark-based infrastructure.

Features: Databricks excels in handling large-scale data analytics, providing a Spark-based environment that offers quick data processing and scalability. It supports machine learning tasks efficiently and includes collaborative notebooks and integrated machine learning libraries. Altair RapidMiner, on the other hand, prioritizes ease of use with its no-code interface, supporting extensive data preparation and delivering initial insights through machine learning and AI tools, which is particularly beneficial for users without programming skills.

Room for Improvement: Databricks could improve by enhancing its visualization capabilities, integrating better with business intelligence tools like Power BI and Tableau, and expanding its machine learning library offerings. Users also suggest enhancing documentation and addressing pricing concerns. Altair RapidMiner would benefit from integrating more machine learning algorithms, enhancing interface support, and improving documentation and support for complex integrations.

Ease of Deployment and Customer Service: Databricks provides robust support for both public and hybrid cloud environments, offering flexible deployment options that suit varying business needs. Its customer service is generally well-received, though response times could be quicker. Altair RapidMiner primarily offers on-premises deployment, limiting flexibility but is praised for its clear documentation that eases initial setup and reduces reliance on technical support.

Pricing and ROI: Databricks faces criticism for high costs, though its pay-per-use model offers value for large workloads and satisfactory ROI due to reduced data processing times. Smaller users, however, may find it expensive. Altair RapidMiner presents a more attractive pricing model with a free option for smaller datasets and competitive rates for professional licenses, appealing to educators and smaller businesses seeking cost-effective advanced analytics solutions.

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 (9th), Streaming Analytics (1st)

Mindshare comparison

As of September 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.4%, down from 7.5% compared to the previous year. The mindshare of Databricks is 14.5%, down from 19.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Databricks	14.5%
Altair RapidMiner	7.4%
Other	78.1%

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

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

"The best part of RapidMiner is efficiency."

"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."

"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."

"I've been using a lot of components from the Strategic Extension and Python Extension."

"The solution is very intuitive and powerful."

"The most valuable feature is what the product sets out to do, which is extracting information and data."

"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

"The most valuable features of the solution are the hardware and the resources it quickly provides without much hassle."

"The setup was straightforward."

"Databricks is definitely a very stable product and reliable."

"The solution is very simple and stable."

"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."

"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."

"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."

"Databricks' most valuable feature is the data transformation through PySpark."

More Databricks pros

Cons

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

"The price of this solution should be improved."

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

"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."

"Improve the online data services."

"In the Mexican or Latin American market, it's kind of pricey."

"I would like to see more integration capabilities."

"A great product but confusing in some way with regard to the user interface and integration with other tools."

More Altair RapidMiner cons

"The Databricks cluster can be improved."

"The biggest problem associated with the product is that it is quite pricey."

"Databricks could improve in some of its functionality."

"The initial setup of Databricks could be complex."

"The API deployment and model deployment are not easy on the Databricks side."

"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."

"In the next release, I would like to see more optimization features."

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

More Databricks cons

Pricing and Cost Advice

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

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

"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."

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

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

"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."

"Databricks are not costly when compared with other solutions' prices."

"The pricing depends on the usage itself."

"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."

"Databricks' cost could be improved."

"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."

More Databricks pricing and cost advice

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Top Industries

By visitors reading reviews

University

11%

Computer Software Company

10%

Manufacturing Company

10%

Educational Organization

10%

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	5
Large Enterprise	8

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

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

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Compared 8% of the time

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Compared 6% of the time

DataRobot vs Altair RapidMiner

Compared 2% of the time

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Compared 9% 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

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Product Reports

Download Altair RapidMiner product report

Altair RapidMiner

September 2025

Download Databricks product report

September 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