Dataiku vs Dremio comparison

Dataiku and Dremio are both solutions in the Data Science Platforms category. Dataiku is ranked #4 with an average rating of 8.0, while Dremio is ranked #11 with an average rating of 8.5. Dataiku holds a 6.7% mindshare in Data Science Platforms, compared to Dremio’s 2.4% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of Dremio users who would recommend it.

Dataiku

Read 17 Dataiku reviews

5,913 Views
5,795 Comparison Views

100% willing to recommend

Dremio

Read 11 Dremio reviews

3,725 Views
2,161 Comparison Views

100% willing to recommend

Dataiku

Dremio

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Executive SummaryUpdated on Feb 15, 2026

Dataiku and Dremio compete in the data management and analytics market. Dataiku offers a more integrated data science platform, favored for its comprehensive workflow and ease of use. Dremio excels in handling complex queries and offers powerful data management capabilities, making it ideal for environments requiring robust data query performance.

Features: Dataiku provides exceptional workflow organization features, integrates seamlessly with multiple programming languages, and offers a suite for machine learning with automation capabilities. In comparison, Dremio stands out in managing data across different sources, supports open-source projects like Arrow and Nessie, and enhances data retrieval with its federated querying abilities.

Room for Improvement: Dataiku could benefit from enhancing its pricing model, improving server stability, and providing better support for non-technical users. It might also improve deep learning integration and add better visualization features. Dremio could improve in areas such as query execution time, particularly for complex queries, and could expand connector availability and interface usability while working on dynamic scaling of clusters.

Ease of Deployment and Customer Service: Dataiku offers versatile deployment options, such as on-premises, private, public, and hybrid cloud environments, providing flexibility, though its customer service receives mixed reviews regarding delays and billing issues. Dremio also supports diverse deployment strategies and is noted for prompt and effective customer service responses.

Pricing and ROI: Dataiku is known for its higher pricing, making it more suitable for larger enterprises, yet it promises a strong ROI through improved data efficiency. Dremio offers a cost-competitive alternative, providing substantial flexible data management benefits, though scaling may lead to higher licensing costs. Both platforms have the potential for positive ROIs, yet pricing remains a key factor in adoption decisions.

To learn more, read our detailed Dataiku vs. Dremio Report (Updated: February 2026).

Buyer's Guide

Dataiku vs. Dremio

February 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

5.4

Dataiku enhances efficiency, compliance, collaboration, and development speed, though financial benefits remain unclear without a pricing change.

Sentiment score

5.6

Dremio reduces manpower costs, enhances efficiency, and eliminates infrastructure concerns, improving operations by accessing multiple data sources.

The market is competitive, and Dataiku must adopt a consumption-based model instead of the current monthly model.

reviewer1525251

Cognitive Business Operation at a consultancy with 10,001+ employees

I consider the return on investment with Dataiku valuable because for us, it is one single platform where all our data scientists come together and work on any model building, so it is collaboration, plus having everything in one place, organized, having proper project management, and then built-in capabilities which help to facilitate model building.

PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

In terms of ROI, the use of Dataiku simplifies the architecture of customers, which helps them to decommission some of their existing tools;

Durgesh-Singh

Head of Delivery & Practice (Data & AI) at a recruiting/HR firm with 201-500 employees

For more quotes and insights, download the Dataiku report

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.

Corrr Moray

SR BI developer at BRQ Digital Solutions

For more quotes and insights, download the Dremio report

Customer Service

Sentiment score

5.8

Dataiku's customer service is praised for responsiveness and expertise but criticized for inconsistency and slow issue resolution.

Sentiment score

5.2

Dremio's customer service is responsive and helpful, facing staffing challenges as demand grows, requiring more integrators for support.

Dataiku partners with local industry experts who understand the business better and provide support.

RichardXu

Data Science Lead at a mining and metals company with 10,001+ employees

The support team does not provide adequate assistance.

reviewer1525251

Cognitive Business Operation at a consultancy with 10,001+ employees

They should not take the complaints so lightly.

PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

For more quotes and insights, download the Dataiku report

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

Corrr Moray

SR BI developer at BRQ Digital Solutions

For more quotes and insights, download the Dremio report

Scalability Issues

Sentiment score

6.2

Dataiku is scalable, integrates with cloud platforms, but some users find room for improvement and are concerned about licensing costs.

Sentiment score

7.1

Dremio scales well, offering flexibility and built-in capabilities, though community users face scaling limits due to licensing.

Dataiku is quite scalable, as long as I can pay for more licenses, there is no technical limitation.

PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

For more quotes and insights, download the Dataiku report

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

Corrr Moray

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

For more quotes and insights, download the Dremio report

Stability Issues

Sentiment score

7.0

Opinions on Dataiku's stability vary, with some reporting issues, while others find it stable under proper management.

Sentiment score

7.2

Dremio is generally stable, scoring high ratings with occasional performance issues, especially with large datasets, requiring maintenance restarts.

In terms of stabilization, if my data has no outlier creation in the raw data, then it is quite stable.

Ravi-Srivastava

Data Scientist at Ericsson

As for stability and reliability, so far so good; after the installation, I really had no problems.

PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

For more quotes and insights, download the Dataiku report

I rate Dremio a nine in terms of stability.

Corrr Moray

SR BI developer at BRQ Digital Solutions

For more quotes and insights, download the Dremio report

Room For Improvement

Dataiku needs improvements in stability, usability, integration, cost-efficiency, and features for smaller teams and non-IT users.

Dremio struggles with Delta connector support, performance issues, SQL limitations, high costs, and fewer connectors than competitors.

Someone who needs to do coding can do it, and someone who does not know coding can also build solutions.

Durgesh-Singh

Head of Delivery & Practice (Data & AI) at a recruiting/HR firm with 201-500 employees

The license is very expensive.

Ramon Roman Viñas

Manager at CTTI - Centre de Telecomunicacions i Tecnologies de la Informació

I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend it by developing and integrating custom components easily with existing ones.

reviewer2667285

Big Data Consultant at a computer software company with 1,001-5,000 employees

For more quotes and insights, download the Dataiku report

Starburst comes with around 50 connectors now.

KamleshPant

Senior Software Architect at USEReady

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.

SyedIsmail

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

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.

Corrr Moray

SR BI developer at BRQ Digital Solutions

For more quotes and insights, download the Dremio report

Setup Cost

Dataiku's pricing ranges from €20 to €40 annually per key, seen as affordable or expensive depending on budgets.

Dremio's pricing, though costly for scaling, is seen as valuable compared to competitors, requiring careful evaluation based on needs.

There are no extra expenses beyond the existing licensing cost.

Ramon Roman Viñas

Manager at CTTI - Centre de Telecomunicacions i Tecnologies de la Informació

I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies.

reviewer2667285

Big Data Consultant at a computer software company with 1,001-5,000 employees

The pricing for Dataiku is very high, which is its biggest downside.

reviewer1525251

Cognitive Business Operation at a consultancy with 10,001+ employees

For more quotes and insights, download the Dataiku report

No quotes available

For more quotes and insights, download the Dremio report

Valuable Features

Dataiku enhances workflows with visual tools, supports multiple languages, and integrates easily with cloud platforms for efficient data management.

Dremio offers efficient data management and visualization with seamless integration, native SQL, and role-based access control features.

This feature is useful because it simplifies tasks and eliminates the need for a data scientist.

RichardXu

Data Science Lead at a mining and metals company with 10,001+ employees

Dataiku primarily enhances the speed at which our customers can develop or train their machine learning models because it is a drag-and-drop platform.

reviewer2667285

Big Data Consultant at a computer software company with 1,001-5,000 employees

It offers most of the capabilities required for data science, MLOps, and LLMOps.

reviewer1525251

Cognitive Business Operation at a consultancy with 10,001+ employees

For more quotes and insights, download the Dataiku report

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

SyedIsmail

Senior Consultant - Data Analytics 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

You just get the source, connect the data, get visualization, get connected, and do whatever you want.

KamleshPant

Senior Software Architect at USEReady

For more quotes and insights, download the Dremio report

Categories and Ranking

Dataiku

Ranking in Data Science Platforms

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Dremio

Ranking in Data Science Platforms

11th

Average Rating

8.4

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (5th)

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Dataiku is 6.7%, down from 12.5% compared to the previous year. The mindshare of Dremio is 2.4%, down from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Dataiku	6.7%
Dremio	2.4%
Other	90.9%

Data Science Platforms

Featured Reviews

PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

Unified platform has accelerated model development and improved collaborative data science work

I think Dataiku could be improved or enhanced in future releases with more 'talk to my data' capabilities, maybe more NLP features, and maybe a platform to build agents. These improvements would benefit me and my processes because they will help us to continue using Dataiku as one platform; right now we are exploring other platforms for the features which are missing, and if they are available within the same platform, I think it will increase the usage of Dataiku further. I think the pricing and licensing of Dataiku is a bit expensive; it could be improved further, and I think they should have a different kind of licensing model as well.

Read full review

Corrr Moray

SR BI developer at BRQ Digital Solutions

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

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

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Energy/Utilities Company

Financial Services Firm

26%

Computer Software Company

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	11

By reviewers
Company Size	Count
Small Business	1
Midsize Enterprise	5
Large Enterprise	5

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

I am not the person involved in the process regarding pricing, setup cost, and licensing.

See all answers

What needs improvement with Dataiku Data Science Studio?

To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is pos...

See all answers

What is your primary use case for Dataiku Data Science Studio?

My main use case for Dataiku is for data science and AI projects. I use Dataiku for a demand forecasting use case where the objective is to predict the demand for each product for the next four mon...

See all answers

What is your experience regarding pricing and costs for Dremio?

I don't have information about pricing, setup cost, and licensing for Dremio, so I am not entitled to discuss it.

See all answers

What needs improvement with Dremio?

I wouldn't say there is anything Dremio can be improved on. If I could change something, I would say many developers and programmers, when they are starting to work in this specific field or area, ...

See all answers

What is your primary use case for Dremio?

I have been using Dremio for a year and a half. My main use case for Dremio is that I am able to access multiple databases and I can easily and quickly connect Dremio with my dashboards. In my rece...

See all answers

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Compared 5% of the time

Amazon SageMaker vs Dremio

Compared 4% of the time

BigQuery vs Dremio

Compared 4% of the time

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Product Reports

Buyer's Guide

Dataiku

February 2026

Download Dataiku product report

Buyer's Guide

Dremio

February 2026

Download Dremio product report

Also Known As

Dataiku DSS

Dremio AWS - BYOL

Overview

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Dataiku

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.

Dremio

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto

UBS, TransUnion, Quantium, Daimler, OVH

Buyer's Guide

Dataiku vs. Dremio

February 2026

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