Amazon SageMaker vs Dataiku comparison

Comparison Buyer's Guide

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: July 2024).

Buyer's Guide

Amazon SageMaker vs. Dataiku

July 2024

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Helped 793,295 peers since 2012

Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of July 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 3.0%, up from 2.3% compared to the previous year. The mindshare of Amazon SageMaker is 8.0%, down from 11.7% compared to the previous year. The mindshare of Dataiku is 12.9%, up from 6.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Unique Categories:

Data Mining

21.6%

AI Development Platforms

7.7%

No other categories found

Featured Reviews

Ali Bin Tahir

Research Executive at NielsenIQ

Mar 1, 2024

Provides comprehensive data analysis and has a simple setup process

We use the product to conduct multiple and diverse statistical analyses across various datasets The software offers consistency across multiple research projects helping us with predictive analytics capabilities. The product’s most valuable capability is to handle large datasets and ensure…

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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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RangeshKunnavakkam

Consultant at Netsoft

May 17, 2024

Gives different aspects of modeling approaches and good for multiple teams' collaboration

I used DataRobot. Dataiku has a different kind of structure to it. It's not financially heavy like DataRobot, which caters more to financial companies, like banks. Dataiku doesn't have that yet. I think they are also working on that area. But yeah, there are some key differences between the two products. DataRobot has an additional feature with financial firms that it creates all these financial metrics when you run a time series analysis. Those things I have not seen in Dataiku. If any financial company is choosing between DataRobot and Dataiku, they will definitely go for DataRobot because it creates all these financial metrics. It creates deltas, time series, time difference fields, and things like that. So, that is an added feature that DataRobot has.

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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

"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."

"It is a modeling tool with helpful automation."

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

"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."

"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."

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

"IBM SPSS Statistics depends on AI."

"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."

More IBM SPSS Statistics pros

"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."

"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."

"Allows you to create API endpoints."

"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 product aggregates everything we need to build and deploy machine learning models in one place."

"We were able to use the product to automate processes."

"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."

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

More Amazon SageMaker pros

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

"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."

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

"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."

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

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

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

"The solution is quite stable."

Cons

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

"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."

"The reports could be better."

"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."

"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."

"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."

"It could allow adding color to data models to make them easier to interpret."

"I think the visualization and charting should be changed and made easier and more effective."

More IBM SPSS Statistics cons

"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."

"The product must provide better documentation."

"The solution needs to be cheaper since it now charges per document for extraction."

"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."

"Lacking in some machine learning pipelines."

"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."

"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."

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

More Amazon SageMaker cons

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

"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 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."

"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."

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

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

More Dataiku cons

Pricing and Cost Advice

"The price of IBM SPSS Statistics could improve."

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

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

"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."

"More affordable training for new staff members."

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

"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."

More IBM SPSS Statistics pricing and cost advice

"The support costs are 10% of the Amazon fees and it comes by default."

"Databricks solution is less costly than Amazon SageMaker."

"The tool's pricing is reasonable."

"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."

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

"Amazon SageMaker is a very expensive product."

"There is no license required for the solution since you can use it on demand."

"The pricing is comparable."

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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793,295 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

University

17%

Educational Organization

13%

Computer Software Company

Financial Services Firm

17%

Educational Organization

14%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

18%

Educational Organization

15%

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?

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

See all answers

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

Pricing is pretty steep. Dataiku is also not that cheap. It depends on the client and how much they want to spend tow...

See all answers

What needs improvement with Dataiku Data Science Studio?

The no-code/low-code aspect, where DataRobot doesn't need much coding at all. Dataiku still needs some coding, and th...

See all answers

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

My current client has Dataiku. We do sentiment analysis and some small large language models right now. We use Dataik...

See all answers

Comparisons

Alteryx vs IBM SPSS Statistics

Compared 16% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 14% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

Weka vs IBM SPSS Statistics

Compared 10% of the time

Anaconda vs IBM SPSS Statistics

Compared 3% of the time

More IBM SPSS Statistics Competitors

Databricks vs Amazon SageMaker

Compared 32% of the time

Azure OpenAI vs Amazon SageMaker

Compared 14% of the time

Google Vertex AI vs Amazon SageMaker

Compared 12% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

DataRobot vs Amazon SageMaker

Compared 3% of the time

More Amazon SageMaker Competitors

Databricks vs Dataiku

Compared 39% of the time

KNIME vs Dataiku

Compared 13% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 9% of the time

Starburst Galaxy vs Dataiku

Compared 1% of the time

More Dataiku Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

July 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Amazon SageMaker

July 2024

Download Amazon SageMaker product report

Buyer's Guide

Dataiku

July 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

July 2024

Free Report: Amazon SageMaker vs. Dataiku

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

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