Dataiku vs Alteryx

by Gralio Feb 21, 2025

Dataiku and Alteryx are data analytics platforms with key differences. Dataiku caters to advanced AI development and deployment. Alteryx prioritizes ease of use and data preparation for a wider user base. Choose Dataiku for robust AI development and Alteryx for accessible data analysis and automation.

At Gralio.ai we help to simplify your decision-making process by offering detailed, side-by-side software comparisons like this one, to help you confidently choose the tool that aligns with your business goals.

This comparison was created by analysing 681 reviews and 60 websites, saving 4 hours, 17 minutes of reading.

Dataiku

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Alteryx

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About

Dataiku is a data science and machine learning platform that helps businesses build and deploy AI solutions. It offers tools for data preparation, visualization, machine learning, and model deployment, all in one place. Dataiku aims to make AI accessible to a wide range of users, from data experts to business users. It's used by companies of all sizes across various industries for applications like predictive maintenance, marketing optimization, and risk management. Dataiku is designed to help businesses scale their AI efforts and make data-driven decisions.

Alteryx is a data analytics platform designed for businesses of all sizes. It offers a user-friendly, drag-and-drop interface to prepare, analyze, and visualize data without needing coding skills. Alteryx excels at automating data tasks, helping you uncover insights faster and make better decisions. It's used across various departments and industries to improve efficiency and gain a competitive advantage.

Summary

Main difference

Dataiku is a comprehensive AI platform for building and deploying AI solutions, ideal for technical users who need advanced features. Alteryx focuses on data preparation, blending, and analysis with a user-friendly interface, making it suitable for a broader range of users, including those without coding skills.

Relative strengths of Dataiku (compared to Alteryx)

Stronger AI and machine learning capabilities for building and deploying models.
Better suited for complex data science projects and model management.
Offers a visual interface with more advanced features for data preparation and analysis.

Relative weaknesses of Dataiku (compared to Alteryx)

Can be more complex to learn and use, especially for non-technical users.
Pricing can be higher, especially for smaller teams.
Performance can be sluggish with very large datasets.

What companies are using Dataiku and Alteryx?

Novartis

No data

Who should use Dataiku VS. Alteryx

Dataiku is a user-friendly platform ideal for enterprises in manufacturing and software, simplifying data management and analysis for building and deploying AI solutions. Users praise its collaborative features and automation capabilities but note performance issues with large datasets. It offers tools for data preparation, visualization, machine learning, and model deployment.

Alteryx is a user-friendly data analytics platform ideal for businesses of all sizes. Its drag-and-drop interface empowers users to prepare, analyze, and visualize data without coding. Users praise its powerful ETL capabilities and seamless integration with platforms like Tableau and Salesforce. However, some users have noted concerns about its pricing and performance with large datasets.

Best fit for enterprise companies.
Ideal for Manufacturing and Software companies.

Best fit for small, medium, and large companies.
Ideal for Retail, Healthcare, Finance, and Marketing.

Dataiku and Alteryx features

Supported

Partially supported

Not supported

Type in the name of the feature or in your own words tell us what you need

Generative AI tools

Supported

Dataiku offers a secure gateway to LLMs, enabling enterprise-scale deployment of generative AI applications with no-code to full-code tools and AI assistants.

Supported

Alteryx offers a secure gateway to LLMs, enabling no-code and full-code generative AI development with AI assistants.
Data visualization tools

Supported

Dataiku offers robust data visualization tools, dashboards, and self-service analytics.

Supported

Alteryx offers basic visualizations and integrates with advanced tools like Power BI and Tableau.
Easy-to-use Interface

Supported

Dataiku offers an intuitive and easy-to-use interface.

Supported

Alteryx offers intuitive interfaces using Interface Tools and Analytic Apps.
BI Tool Integration

Supported

Dataiku integrates with BI tools like Tableau, Power BI, and Looker.

Supported

Alteryx integrates with BI tools like Tableau and Power BI.
Data cleaning

Supported

Dataiku can clean data, remove duplicates, fix data types, and handle errors.

Supported

Alteryx can clean data, remove duplicates, fix data types, and handle errors.
SQL data transformation

Supported

Dataiku allows data transformations using SQL queries within its platform.

Partially supported

Alteryx supports SQL transformations indirectly via in-database tools, not directly.

Qualities

Value and Pricing Transparency

-1

Strongly negative sentiment

-0.75

Strongly negative sentiment
Customer Service

No data

+0.5

Rather positive sentiment
Ease of Use

+0.82

Strongly positive sentiment

+0.96

Strongly positive sentiment
Reliability and Performance

-0.2

Neutral sentiment

+0.49

Rather positive sentiment
Ease of Implementation

+0.6

Rather positive sentiment

+0.33

Rather positive sentiment
Scalability

No data

+0.66

Rather positive sentiment

Dataiku and Alteryx Pricing

No data

User sentiment

Strongly negative

-1

See full Pricing page

No data

User sentiment

Strongly negative

-0.75

See full Pricing page

Dataiku and Alteryx review insights

681 reviews analysed from and

Users love

User-friendly interface simplifies data management and analysis.
Excellent collaboration features.
Effective for building and refining project management documents.
Automates repetitive tasks like model deployment and report generation.
Intuitive UI enables business users to interact with data and perform advanced analytics.

User-friendly drag-and-drop interface enables both technical and non-technical users to perform complex data transformations without coding.
Powerful for ETL tasks, blending, analyzing, and preparing data from multiple sources quickly.
Integrates well with other platforms, including Tableau and Salesforce.
Offers automation for repetitive workflows, enhancing productivity and scalability.

Users dislike

Sluggish performance with large datasets.
Limited data visualization capabilities.
High processing charges.
Steep learning curve for advanced features.
Resource intensive, requiring robust hardware.

Pricing: Alteryx can be expensive, especially for small teams or organizations, with advanced features locked behind higher-priced plans.
Performance can be slow when working with very large datasets.
Advanced functionalities can be challenging to learn for users with limited technical backgrounds.
Limited real-time collaboration features make it harder for teams to work simultaneously on the same workflow.

Dataiku and Alteryx Ratings

G2

4.3/5

(48)
Capterra

4.7/5

(12)
Glassdoor

3.6/5

(489)

G2

4.6/5

(627)
Glassdoor

3.3/5

(790)

Company health

Employee growth

6% increase in the last year

16% decrease in the last year

Web traffic

10% decrease in the last quarter

7% decrease in the last quarter

Financing

August 2022 - $847M

September 2023 - $1B

How do Dataiku's generative AI tools compare to Alteryx's automated analytics?

Dataiku's generative AI tools focus on enabling users to build and deploy generative AI applications, offering a secure gateway to LLMs with no-code to full-code tools and AI assistants. Alteryx, on the other hand, emphasizes automated analytics, streamlining data preparation, analysis, and reporting through automated workflows. While both platforms aim to improve efficiency, Dataiku leans towards generative AI application development, while Alteryx focuses on broader automated data analysis processes.

Which platform, Dataiku or Alteryx, better supports non-coding business users?

Alteryx better supports non-coding business users. Its drag-and-drop interface and focus on automation reduce the need for coding skills, while Dataiku, despite aiming for broader accessibility, still caters more to data professionals with its emphasis on model deployment and advanced analytics. Alteryx's higher ease-of-use score further reinforces its suitability for non-coders.

What are the advantages of Dataiku?

Dataiku offers a broader range of functionalities encompassing data preparation, visualization, machine learning, and model deployment within a single platform, making it advantageous for end-to-end AI solution development. Its focus on accessibility for both technical and business users through a user-friendly interface simplifies data interaction and advanced analytics. Furthermore, Dataiku provides specific tools for generative AI, enabling enterprise-scale deployment of these applications.

What are the disadvantages of Dataiku?

Dataiku can suffer from performance issues, especially with large datasets, leading to slow processing times. Some users find its advanced features have a steep learning curve. The platform can be resource-intensive, requiring powerful hardware. Finally, Dataiku's data visualization capabilities have been criticized as limited compared to other platforms.

Alternatives to Dataiku and Alteryx

Tableau

Tableau is a popular data analytics platform that helps businesses make sense of their data. It offers powerful, user-friendly tools for visualizing data, creating interactive dashboards, and sharing insights across your organization. Tableau is suitable for companies of all sizes and is known for its intuitive drag-and-drop interface, even for non-technical users. It allows you to connect to various data sources, analyze information visually, and discover trends to make better business decisions.

SAS Viya

SAS Viya is a cloud-based data analytics platform designed to help businesses of all sizes make better decisions through data insights. It offers a wide range of tools for data management, analysis, and modeling, including machine learning and artificial intelligence capabilities. SAS Viya allows users to access and analyze data from various sources, build and deploy predictive models, and share insights through interactive dashboards and reports. Its focus is to provide a comprehensive platform for data professionals and business users to collaborate and extract value from their data, enabling faster and more informed decision-making.

DataRobot

DataRobot is an AI platform designed to make data science accessible for businesses of all sizes. It automates the process of building, deploying, and managing machine learning models. This allows companies to uncover insights from their data and make better decisions, even without extensive data science expertise. DataRobot is particularly known for its ability to build accurate predictive models and for its user-friendly platform that simplifies the complexities of AI.

Spotfire

Spotfire is a visual analytics platform that helps businesses make better decisions using their data. It offers a user-friendly interface with drag-and-drop functionality and advanced features like predictive modeling and AI insights, making complex data analysis accessible, even without coding experience. Spotfire excels in industries with large datasets, providing tailored solutions and visualizations for specific business challenges.

SAP HANA Cloud

SAP HANA Cloud is a comprehensive database service designed for modern, data-driven applications. It allows you to store, manage, and analyze all types of data in one place. Its strength lies in handling large data volumes quickly, making it ideal for real-time reporting and analysis. SAP HANA Cloud also offers built-in tools for data science and machine learning, enabling you to uncover deeper insights and make smarter business decisions. Its cloud-native architecture means it's scalable, secure, and requires minimal IT management, letting you focus on results, not infrastructure.

RapidCanvas

RapidCanvas is an AI platform designed for business users without coding or data science experience. It uses automation to help you build custom AI solutions, going from raw data to usable predictions quickly. The platform offers automated data analysis, model creation, and insights generation, all visually presented. RapidCanvas is suited for mid-sized to large companies in industries like manufacturing and finance, aiming to streamline processes and improve decision-making.

Page co-authored by

Michal Kaczor

CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

Tymon Terlikiewicz

CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.

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