Dataiku vs Dremio comparison

Why PeerSpot?

Dataiku and Dremio are both solutions in the Data Science Platforms category. Dataiku is ranked #2 with an average rating of 8.3, while Dremio is ranked #9 with an average rating of 8.1. Dataiku holds a 4.4% mindshare in Data Science Platforms, compared to Dremio’s 2.0% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of Dremio users who would recommend it.

Dataiku

Read 21 Dataiku reviews

7,894 Views
7,736 Comparison Views

100% willing to recommend

Dremio

Read 14 Dremio reviews

4,948 Views
2,523 Comparison Views

100% willing to recommend

Dataiku

Dremio

Comparison Buyer's Guide

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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: September 2026).

Buyer's Guide

Dataiku 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

4.9

Dataiku streamlines cross-functional projects for data scientists, enhancing compliance and suggesting a shift to consumption-based pricing.

Sentiment score

4.0

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

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

It is a good return on investment since it helps save a lot of time, and it's easy for my teammates to work cross-functionally on the same project.

reviewer2811273

Data Scientist at a tech vendor with 51-200 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

5.3

Dataiku customer service offers quick responses and varying support experiences, with local partnerships aiding in industry-specific assistance.

Sentiment score

6.1

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

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

I would rate customer support a ten out of ten.

reviewer2913786

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.

Corrr Moray

SR BI developer at BRQ Digital Solutions

For more quotes and insights, download the Dremio report

Scalability Issues

Sentiment score

5.8

Dataiku offers scalable solutions with cloud integration, supporting expansion and seamless team adaptation, despite minor performance concerns with large data.

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.

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

Dataiku's scalability is pretty good; I can scale the projects very easily, and clear guidance is given as well.

Manikya Arora

Solution Architect at a pharma/biotech company with 10,001+ employees

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

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

reviewer2913786

Director

For more quotes and insights, download the Dremio report

Stability Issues

Sentiment score

6.9

Dataiku is stable for most users, though some experience issues with complex tasks, updates, and data quality variations.

Sentiment score

7.2

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

It would help if there was a backup proposition in place to avoid hampering our work due to updates.

Shubhamkumar Gomar

Senior Data Scientist at Deloitte

For around ten percent of the day, it is usually down, and we are unable to do work on it.

reviewer2811273

Data Scientist at a tech vendor with 51-200 employees

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

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

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

For more quotes and insights, download the Dremio report

Room For Improvement

Dataiku faces challenges like high cost, complex interface, and limited support, requiring improvements in integration, visualization, and documentation.

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

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

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.

reviewer2913786

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

For more quotes and insights, download the Dremio report

Setup Cost

Dataiku's pricing is high and varies, with enterprise expense concerns, yet it's relatively affordable for large companies.

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

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

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.

reviewer2913786

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

For more quotes and insights, download the Dremio report

Valuable Features

Dataiku offers intuitive tools for data preparation and integration, supporting collaboration, scalability, and efficiency for diverse teams.

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

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.

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

Dataiku

Ranking in Data Science Platforms

2nd

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

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 Dataiku is 4.4%, down from 10.5% 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 (%)
Dataiku	4.4%
Dremio	2.0%
Other	93.6%

Data Science Platforms

Featured Reviews

Shubhamkumar Gomar

Senior Data Scientist at Deloitte

Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly

In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.

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

18%

Manufacturing Company

10%

Computer Software Company

Comms Service Provider

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	6
Midsize Enterprise	2
Large Enterprise	13

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 Dataiku Data Science Studio?

The licenses are a bit high for companies that are still hesitating to get started with using Dataiku. For my personal projects, I used the thirty-day free trial. Regarding my company, I did not ha...

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What needs improvement with Dataiku Data Science Studio?

I have no suggestions for improvements because it's all good; it just sometimes lags a lot, and I don't know if the server is full or what, but it sometimes takes a lot of time while loading and re...

See all answers

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

My main use case for Dataiku involves ETL pipelines, mainly for data analysis, and I majorly use SQL queries for that. For ETL pipelines and data analysis, I had to create the output by combining a...

See all answers

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.

See all answers

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...

See all answers

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...

See all answers

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Compared 14% of the time

Snowflake vs Dremio

Compared 12% of the time

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Compared 4% of the time

Starburst Enterprise vs Dremio

Compared 3% of the time

Amazon SageMaker vs Dremio

Compared 3% of the time

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Product Reports

Buyer's Guide

Dataiku

October 2026

Download Dataiku product report

Buyer's Guide

Dremio

October 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

September 2026

Free Report: Dataiku vs. Dremio

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