Altair RapidMiner vs Dremio comparison

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Altair RapidMiner

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Executive SummaryUpdated on Jun 3, 2026

Altair RapidMiner and Dremio compete in the data analysis and management category. Altair RapidMiner leads in pricing and user satisfaction, while Dremio excels in robust capabilities and comprehensive features, justifying its investment.

Features: Altair RapidMiner offers a powerful data science platform with data preparation, machine learning capabilities, and an intuitive GUI for model deployment. Dremio provides data virtualization, integration capabilities for multiple data sources, and an efficient query system for easy data access and transformation.

Room for Improvement: Altair RapidMiner could enhance integration with more advanced analytics tools and improve real-time data processing. Additionally, expanding community support for advanced generative AI models would be beneficial. Dremio would benefit from simplifying its deployment process and providing more comprehensive user training. Improved integration with more third-party visualization tools and reducing complexity in its federated query system would enhance user experience.

Ease of Deployment and Customer Service: Altair RapidMiner provides an easy-to-deploy platform with responsive service that helps in quick user adaptation and problem resolution. Dremio offers a more detailed deployment process aligning with its data integration capabilities, combined with solid customer support that addresses complex queries effectively.

Pricing and ROI: Altair RapidMiner generally offers an accessible pricing structure, providing favorable ROI due to its straightforward costs and efficiency for data science tasks. Dremio often entails a higher initial investment, yet its advanced features and integration potentials may result in a higher long-term ROI for users that fully leverage its capabilities.

To learn more, read our detailed Altair RapidMiner vs. Dremio Report (Updated: September 2026).

Altair RapidMiner vs. Dremio

September 2026

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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:

ROI

Sentiment score

8.0

Altair RapidMiner's initial high cost is offset by long-term savings and high ROI, with users appreciating its value.

Sentiment score

4.0

Dremio offers cost savings and efficiency by reducing infrastructure needs and simplifying data source integration on data lakes.

The utilities predictive maintenance return on investment I mentioned, with a twenty percent reduction in unplanned downtime, is the clearest example.

Satesh P

Solution Architect at Hitachi Digital Services

I have seen a return on investment, as the defect reduction and forecast accuracy improvements have tangible financial value, with the scrap reduction alone recovering a significant portion of the platform cost in the first year.

For more quotes and insights, download the Altair RapidMiner report

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

Dremio surely saves time, reduces costs, and all those things because we don't have to worry so much about the infrastructure to make the different tools communicate.

For more quotes and insights, download the Dremio report

SR BI developer at BRQ Digital Solutions

Customer Service

Sentiment score

6.8

Altair RapidMiner's customer service is praised for community resources, though direct support response times can vary.

Sentiment score

6.1

Dremio's customer service is highly praised for responsiveness, with Gold plan users enjoying positive interactions despite some limitations.

I have not encountered any problems with Altair RapidMiner technical support.

Professor at Instituto Superior de Contabilidade e Administraçao de Coimbra

the technical documentation is thorough

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

I would rate customer support a ten out of ten.

Director

We contact the technical support at least weekly; currently, it's more or less daily because we face performance issues, crashes of queries sometimes, and we also need support for configuration of the query engines and so on.

Baptiste Bergelin

Data Architect at a consultancy with 51-200 employees

We have had to reach out for customer support many times, and they respond, so they are pretty supportive about some long-term issues.

For more quotes and insights, download the Dremio report

SR BI developer at BRQ Digital Solutions

Scalability Issues

Sentiment score

6.2

Altair RapidMiner scales efficiently for machine learning, though complex operations may need guidance, with scalability and load balance as key interests.

Sentiment score

7.3

Dremio's scalability excels, with user-configurable auto-scaling on Kubernetes/Docker, meeting large-scale needs, but some features require licensing.

No quotes available

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Dremio's scalability can handle growing data and user demands easily.

SR BI developer at BRQ Digital Solutions

Internally, if it's on Docker or Kubernetes, scalability will be built into the system.

KamleshPant

Senior Software Architect at USEReady

Dremio's scalability depends on your hardware and your deployment.

For more quotes and insights, download the Dremio report

Director

Stability Issues

Sentiment score

7.3

Altair RapidMiner is celebrated for its stability and reliability, with occasional minor issues, rated 8-9 out of 10.

Sentiment score

7.2

Dremio users report stable performance overall, despite occasional memory leaks, scalability issues, and the need for frequent monitoring.

Altair RapidMiner is stable with no issues of downtime or crashes.

Professor at Instituto Superior de Contabilidade e Administraçao de Coimbra

Altair RapidMiner is a stable product, and it has been smooth to use without any bugs or issues.

For more quotes and insights, download the Altair RapidMiner report

Senior Manager, Digitalization of Supply Chain& Traceability at a non-profit with 501-1,000 employees

I rate Dremio a nine in terms of stability.

For more quotes and insights, download the Dremio report

SR BI developer at BRQ Digital Solutions

We refactored the query, and that worked, but it still doesn't make you confident to go to production with a product that might crash depending on the query you send it.

Baptiste Bergelin

Data Architect at a consultancy with 51-200 employees

Room For Improvement

Altair RapidMiner users desire improved UI, tool integration, pricing, deep learning, documentation, security, automation, and open-source adoption.

Dremio users face issues with performance, connectors, learning curve, and desire better integration and schema flexibility.

Incorporating generative AI as an AI assistant would be beneficial.

Professor at Instituto Superior de Contabilidade e Administraçao de Coimbra

It would be beneficial if the platform could suggest suitable AI models and provide more advanced AI features.

Senior Manager, Digitalization of Supply Chain& Traceability at a non-profit with 501-1,000 employees

Graph Studio and knowledge graph capabilities are powerful in theory, but the learning curve is steep.

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

Starburst comes with around 50 connectors now.

KamleshPant

Senior Software Architect at USEReady

Before we wrap up, I want to add that Dremio is lacking a semantic layer in a manner that the user can just choose dimensions, metrics, and filters to query the data.

For more quotes and insights, download the Dremio report

Director

It should be easier to get Arctic or an open-source version of Arctic onto the software version so that development teams can experiment with it.

reviewer2769915

Data Consultant at a comms service provider with 201-500 employees

Setup Cost

Altair RapidMiner offers a flexible pricing model, perceived as expensive but more affordable than SAS or SPSS, with educational benefits.

Dremio offers cost-effectiveness but licensing is costly, leading some users to prefer the community version for scalability.

The licensing model is flexible in the sense that you can apply units across different products.

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

We are likely to purchase a license, which may offer additional features.

For more quotes and insights, download the Altair RapidMiner report

Senior Manager, Digitalization of Supply Chain& Traceability at a non-profit with 501-1,000 employees

I chose eight out of ten because Dremio is expensive for the Enterprise version, particularly regarding licensing.

Burak Uğur

Data Engineer at a tech services company with 201-500 employees

I had a good experience with pricing, as the pricing seems okay to me and the client.

For more quotes and insights, download the Dremio report

Director

Dremio does have a core of the engine that is open-source, but all the important features for the enterprise version are under license.

Baptiste Bergelin

Data Architect at a consultancy with 51-200 employees

Valuable Features

Altair RapidMiner simplifies building ML pipelines with no-code workflows, data integration, and seamless Python/R integration for organizations.

Dremio excels in data virtualization, federated queries, and integration, enhancing data management and access with efficient tools.

Building complete machine learning pipelines, data ingestion, transformation, feature engineering, model training, validation, and deployment in a drag-and-drop visual environment without extensive coding is what makes this accessible to organizations that cannot staff a team of Python developers for every analytics project.

Satesh P

Solution Architect at Hitachi Digital Services

Altair RapidMiner is appreciated for its ease of use and the CRISP data mining model it supports, covering steps like data preparation, data understanding, and business understanding.

Professor at Instituto Superior de Contabilidade e Administraçao de Coimbra

Altair RapidMiner is easy to use and intuitive with no coding required, making it a low code tool.

For more quotes and insights, download the Altair RapidMiner report

Senior Manager, Digitalization of Supply Chain& Traceability at a non-profit with 501-1,000 employees

Having everything under one system and an easier-to-work-with interface, along with having API integrations, adds significant value to working with Dremio.

reviewer2769915

Data Consultant at a comms service provider with 201-500 employees

Dremio has positively impacted my organization as nowadays we are connected to multiple databases from multiple environments, multiple APIs, and applications, and Dremio organizes everything in an amazing way for me.

Joao Silveira

Data Analyst at a insurance company with 501-1,000 employees

Multiple data sources can be queried in one query, and it is not just a query engine.

Burak Uğur

Data Engineer at a tech services company with 201-500 employees

For more quotes and insights, download the Dremio report

Categories and Ranking

Altair RapidMiner

Ranking in Data Science Platforms

11th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Predictive Analytics (6th)

Dremio

Ranking in Data Science Platforms

9th

Average Rating

8.4

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (10th)

Mindshare comparison

As of November 2026, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 3.3%, down from 6.5% compared to the previous year. The mindshare of Dremio is 2.0%, down from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dremio	2.0%
Altair RapidMiner	3.3%
Other	94.7%

Data Science Platforms

Featured Reviews

Satesh P

Solution Architect at Hitachi Digital Services

Visual workflows have empowered teams to build and deploy reliable predictive maintenance models

The best features Altair RapidMiner offers in my experience are the visual workflow designer in AI Studio, which is the foundation of everything. Building complete machine learning pipelines, data ingestion, transformation, feature engineering, model training, validation, and deployment in a drag-and-drop visual environment without extensive coding is what makes this accessible to organizations that cannot staff a team of Python developers for every analytics project. That capability opens the door.Auto Model is the feature I lean on most when doing rapid prototyping with clients. It evaluates multiple algorithms automatically, surfaces the best-performing model for the data, and explains why. That dramatically compresses the experimentation phase. What would take a data scientist days of manual testing, Auto Model does in an hour.

Read full review

Has simplified complex data integration workflows and supported consistent reporting across multiple sources

SR BI developer at BRQ Digital Solutions

We also have a close relationship with the team that does the Dremio maintenance for the database, like upgrading the versions and they know about some specific problems we had in the past, such as a memory leak. We had a memory leak on some versions, which sometimes stopped the service. Since we are using Dremio installed like a server, not a SaaS solution, many times we need to stop and restart the service to clear all the cache and all that, and this is the thing I should add. I see that many times the new versions of Dremio have not fixed old bugs, and in some new versions, old problems that were previously fixed come back again, so I think the upgrade part could use improvement. I remember using some features in the past, like pivot tables, which proved to be really difficult, but I know this is a fault also for other vendors. Pivoting, transposing, and unpivoting are often not so good. CTEs also many times prove to be not so good, so I think these two main items could be improved significantly if they standardize them.

Read full review

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Top Industries

By visitors reading reviews

Manufacturing Company

13%

Financial Services Firm

11%

University

Educational Organization

Financial Services Firm

22%

Outsourcing Company

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	5
Large Enterprise	10

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	6
Large Enterprise	5

Questions from the Community

What is your experience regarding pricing and costs for RapidMiner?

My experience with pricing, setup cost, and licensing shows that the licensing model is based on Altair Units, which is their shared token-based system across their product portfolio and is flexibl...

What needs improvement with RapidMiner?

Altair RapidMiner can be improved by enhancing the newer GenAI features, which are interesting but honestly still quite early, and the documentation does not yet match the ambition of what they are...

What is your primary use case for RapidMiner?

My main use case for Altair RapidMiner is predictive quality analysis on the manufacturing site, as Wagner Spraytech manufactures spray finishing equipment and we generate a significant amount of o...

What is your experience regarding pricing and costs for Dremio?

I chose eight out of ten because Dremio is expensive for the Enterprise version, particularly regarding licensing.

What needs improvement with Dremio?

I think Dremio can be improved to query faster than multiple sources and big data lakehouses. The community version could be updated for new data catalog connections. I think the documentation is s...

What is your primary use case for Dremio?

I have been using Dremio to select multiple data sources, retrieve multiple data sources, and create and maintain Iceberg tables for the data lakehouse. My main use case for Dremio is to actively c...

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Product Reports

Download Altair RapidMiner product report

Altair RapidMiner

October 2026

Download Dremio product report

October 2026

Also Known As

No data available

Dremio AWS - BYOL

Overview

Altair RapidMiner is a GUI-driven, code-free data science tool ideal for users seeking efficiency and user-friendliness, featuring automated data cleaning and versatile model support for diverse tasks.

Altair RapidMiner offers an accessible platform with drag-and-drop functionality, supporting multiple file formats to streamline data science workflows. It enables quick prototyping and integrates with APIs, Python, and R, enhancing user flexibility. Comprehensive documentation and tutorials support learning, while features like model fine-tuning and predictive analytics cater to advanced analysis. Enhancements in automation and deep learning, alongside improvements in data service integration and metadata handling, remain a focus for development.

What are the key features of Altair RapidMiner?

Code-Free Interface: Simplifies data science with GUI support.
Drag-and-Drop Functionality: Streamlines process setup.
Automated Data Cleaning: Saves time in data preparation.
Machine Learning Algorithms: Supports a wide range for various tasks.
API & Python/R Integration: Enhances flexibility for data projects.
Tutorials & Documentation: Provides robust learning resources.

What benefits and ROI can users expect?

Efficiency: Reduces time spent on data processing.
Flexibility: Offers adaptable integration options.
Scalability: Suited for both educational and business environments.
Usability: User-friendly interface encourages wider adoption.
Predictive Capabilities: Empowers advanced business analytics.

Industries such as telecom and finance utilize Altair RapidMiner for tasks like data preparation and forecasting. Universities employ it for education and research projects, while businesses apply it to areas such as financial crime management and market analysis. It assists companies in predicting customer behavior and analyzing pharmaceutical data, allowing seamless integration with other systems.

Altair

Dremio offers a comprehensive platform for data warehousing and data engineering, integrating seamlessly with data storage systems like Amazon S3 and Azure. Its main features include scalability, query federation, and data reflection.

Dremio's core strength lies in its ability to function as a robust data lake query engine and data warehousing solution. It facilitates the creation of complex queries with ease, thanks to its support for Apache Airflow and query federation across endpoints. Despite challenges with Delta connector support, complex query execution, and expensive licensing, users find it valuable for managing ad-hoc queries and financial data analytics. The platform aids in SQL table management and BI traffic visualization while reducing storage costs and resolving storage conflicts typical in traditional data warehouses.

What are Dremio's most valuable features?

Native Error Interfaces: Simplifies error detection and troubleshooting
Integration with Apache Airflow: Enhances workflow automation capabilities
Scalability: Effortlessly handles growing data demands
Role-Based Access Management: Provides secure data access control
Data Reflection: Optimizes query performance automatically
Query Federation: Supports queries across multiple endpoints seamlessly
Data Cataloging and Virtualization: Offers streamlined data organization

What benefits and ROI should users look for?

Reduced Data Storage Costs: Efficiently manages data to minimize storage expenses
Improved Query Performance: Enhances processing speed for large datasets
Flexibility in Integration: Easily connects with storage solutions like Oracle and MySQL
Enhanced Data Management: Supports comprehensive data analysis workflows

Dremio is primarily implemented in industries requiring extensive data engineering and analytics, including finance and technology. Companies use it for constructing data frameworks, efficiently processing financial analytics, and visualizing BI traffic. It acts as a viable alternative to AWS Glue and Apache Hive, integrating seamlessly with multiple databases, including Oracle and MySQL, offering robust solutions for data-driven strategies. Despite some challenges, its ability to reduce data storage costs and manage complex queries makes it a favorable choice among enterprise users.

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

UBS, TransUnion, Quantium, Daimler, OVH