Dataiku vs Domino Data Science Platform comparison

Dataiku and Domino Data Lab are both solutions in the Data Science Platforms category. Dataiku is ranked #7 with an average rating of 7.5, while Domino Data Lab is ranked #20. Dataiku holds a 11.5% mindshare in Data Science Platforms, compared to Domino Data Lab’s 2.7% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of Domino Data Lab users who would recommend it.

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Executive Summary

We performed a comparison between Dataiku and Domino Data Science Platform based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Knime, Microsoft and others in Data Science Platforms.

To learn more, read our detailed Data Science Platforms Report (Updated: October 2024).

Buyer's Guide

Data Science Platforms

October 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Dataiku is 11.5%, up from 7.5% compared to the previous year. The mindshare of Domino Data Science Platform is 2.7%, up from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

Sep 21, 2023

Enhancing survey analysis that provides valued insightfulness

I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…

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Sabrine Bendimerad

Data Scientist at Electricite De France

Jun 11, 2024

Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms

One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.

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Syed-Hussain

Senior Consultant - IT Business Applications at ADM

Nov 27, 2019

Good scalability and stability but the predictive analysis feature needs improvement

We primarily use the solution for customer retention, but there are a lot of use cases for this particular product The analysis capabilities are the solution's most valuable feature. The predictive analysis feature needs improvement. I've been using the solution for six months. I'd rate the…

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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 most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."

"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."

"It offers very good visualization."

"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."

"The most valuable feature is the user interface because you don't need to write code."

"in terms of the simplicity, I think the SPSS basic can handle it."

"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."

"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."

More IBM SPSS Statistics pros

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."

"The most valuable feature is the set of visual data preparation tools."

"The solution is quite stable."

"Data Science Studio's data science model is very useful."

"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."

"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."

"Cloud-based process run helps in not keeping the systems on while processes are running."

More Dataiku pros

"The scalability of the solution is good; I'd rate it four out of five."

Cons

"The design of the experience can be improved."

"The solution needs to improve forecasting using time series analysis."

"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."

"The solution needs more planning tools and capabilities."

"This solution is not suitable for use with Big Data."

"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."

"There is a learning curve; it's not very steep, but there is one."

"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."

More IBM SPSS Statistics cons

"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."

"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."

"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."

"The ability to have charts right from the explorer would be an improvement."

"I think it would help if Data Science Studio added some more features and improved the data model."

More Dataiku cons

"The predictive analysis feature needs improvement."

Pricing and Cost Advice

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"The price of this solution is a little bit high, which was a problem for my company."

"It's quite expensive, but they do a special deal for universities."

"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."

"I rate the tool's pricing a five out of ten."

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

"The price of IBM SPSS Statistics could improve."

More IBM SPSS Statistics pricing and cost advice

"Pricing is pretty steep. Dataiku is also not that cheap."

"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

University

10%

Computer Software Company

Manufacturing Company

Financial Services Firm

18%

Educational Organization

16%

Manufacturing Company

Computer Software Company

Financial Services Firm

31%

Manufacturing Company

11%

Computer Software Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Statistics?

While the pricing of the product may be higher, the accompanying service and features justify the investment. However...

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What needs improvement with IBM SPSS Statistics?

In some cases, the product takes time to load a large dataset. They could improve this particular area.

See all answers

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

It is very expensive.

See all answers

What needs improvement with Dataiku Data Science Studio?

One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integratin...

See all answers

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

We use the solution for data science and machine learning.

See all answers

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Comparisons

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

KNIME vs IBM SPSS Statistics

Compared 3% of the time

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Databricks vs Dataiku

Compared 38% of the time

KNIME vs Dataiku

Compared 14% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 11% of the time

IBM SPSS Modeler vs Dataiku

Compared 1% of the time

More Dataiku Competitors

Amazon SageMaker vs Domino Data Science Platform

Compared 36% of the time

Databricks vs Domino Data Science Platform

Compared 29% of the time

Microsoft Azure Machine Learning Studio vs Domino Data Science Platform

Compared 7% of the time

Alteryx vs Domino Data Science Platform

Compared 6% of the time

KNIME vs Domino Data Science Platform

Compared 6% of the time

More Domino Data Science Platform Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

October 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Dataiku

November 2024

Download Dataiku product report

Buyer's Guide

Data Science Platforms

October 2024

Download Domino Data Science Platform product report

Also Known As

SPSS Statistics

Dataiku DSS

Domino Data Lab Platform

Learn More

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Dataiku

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Domino Data Lab

Interactive Demo

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Dataiku

Domino Data Lab

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

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.

Domino provides a central system of record that keeps track of all data science activity across an organization. Domino helps data scientists seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk.

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA

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

Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life

Buyer's Guide

Data Science Platforms

October 2024

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