Amazon SageMaker vs Dataiku comparison

Amazon Web Services (AWS) and Dataiku are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #5 with an average rating of 7.6, while Dataiku is ranked #7 with an average rating of 7.5. Amazon Web Services (AWS) holds a 7.7% mindshare in Data Science Platforms, compared to Dataiku’s 11.5% mindshare. Additionally, 89% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Dataiku users who would recommend it.

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Amazon SageMaker and Dataiku based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Amazon SageMaker vs. Dataiku Report (Updated: October 2024).

Buyer's Guide

Amazon SageMaker vs. Dataiku

October 2024

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Helped 815,854 peers since 2012

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 Amazon SageMaker is 7.7%, down from 10.4% compared to the previous year. The mindshare of Dataiku is 11.5%, up from 7.5% 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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Natu Lauchande

Tech Lead - Sanlam Fintech Cluster - Data,ML,AI Eng. at Sanlam

Feb 27, 2024

Easy to use and manage, but the documentation does not have a lot of information

We use the product for deploying machine learning models. We use it for the machine learning model development process We're currently implementing a project on a cross-selling model. It is like a standard XGBoost model. I’m evaluating the tool to see whether it will improve the workflow.…

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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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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 feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

"It has the ability to easily change any variable in our research."

"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."

"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."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."

"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

More IBM SPSS Statistics pros

"Allows you to create API endpoints."

"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."

"Amazon SageMaker is highly valuable for managing ML workloads. It connects to AWS cloud resources, making it easy to deploy algorithms and collaborate using tools like GitLab. It offers a wide range of Python libraries and other necessary tools for modelling and algorithms."

"The technical support of the tool was good."

"The few projects we have done have been promising."

"The most tool's valuable feature, in my experience, is hyperparameter tuning. It allows us to test different parameters for the same model in parallel, which helps us quickly identify the configuration that yields the highest accuracy. This parallel computing capability saves us a lot of time."

"The most valuable feature of Amazon SageMaker is SageMaker Studio."

"We've had no problems with SageMaker's stability."

More Amazon SageMaker pros

"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 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."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

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

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

"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."

"The solution is quite stable."

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

More Dataiku pros

Cons

"It could provide even more in the way of automation as there are many opportunities."

"The statistics should be more self-explanatory with detailed automated reports."

"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."

"The technical support should be improved."

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

"Needs more statistical modelling functions."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

"The solution needs more planning tools and capabilities."

More IBM SPSS Statistics cons

"SageMaker would be improved with the addition of reporting services."

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

"The documentation must be made clearer and more user-friendly."

"When starting a new session, the waiting time can be quite long, ranging from two to five minutes."

"The model repository is a concern as models are stored on a bucket and there's an issue with versioning."

"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."

"There are other better solutions for large data, such as Databricks."

"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."

More Amazon SageMaker cons

"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."

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

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

"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."

More Dataiku cons

Pricing and Cost Advice

"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."

"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 IBM SPSS Statistics could improve."

"We think that IBM SPSS is expensive for this function."

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

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

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

"More affordable training for new staff members."

More IBM SPSS Statistics pricing and cost advice

"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."

"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

"I would rate the solution's price a ten out of ten since it is very high."

"The tool's pricing is reasonable."

"Amazon SageMaker is a very expensive product."

"The pricing is comparable."

"The product is expensive."

More Amazon SageMaker pricing and cost advice

"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."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

University

Computer Software Company

Manufacturing Company

Financial Services Firm

18%

Educational Organization

14%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

18%

Educational Organization

16%

Manufacturing Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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...

See all answers

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

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designe...

See all answers

What do you like most about Amazon SageMaker?

We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to Cha...

See all answers

What is your experience regarding pricing and costs for Amazon SageMaker?

The license cost for Amazon SageMaker ranges between seven thousand to fifteen thousand dollars per month depending o...

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

Comparisons

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 14% 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 2% of the time

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Databricks vs Amazon SageMaker

Compared 27% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Google Vertex AI vs Amazon SageMaker

Compared 11% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

Hugging Face vs Amazon SageMaker

Compared 4% of the time

More Amazon SageMaker Competitors

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

Product Reports

Buyer's Guide

IBM SPSS Statistics

November 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Amazon SageMaker

November 2024

Download Amazon SageMaker product report

Buyer's Guide

Dataiku

November 2024

Download Dataiku product report

Also Known As

SPSS Statistics

AWS SageMaker, SageMaker

Dataiku DSS

Learn More

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IBM

Amazon Web Services (AWS)

Dataiku

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.”

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

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.

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

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

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

Buyer's Guide

Amazon SageMaker vs. Dataiku

October 2024

Free Report: Amazon SageMaker vs. Dataiku

Find out what your peers are saying about Amazon SageMaker vs. Dataiku and other solutions. Updated: October 2024.

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