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 #3 with an average rating of 7.9, while Dataiku is ranked #7 with an average rating of 7.5. Amazon Web Services (AWS) holds a 7.5% mindshare in Data Science Platforms, compared to Dataiku’s 11.8% mindshare. Additionally, 90% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Dataiku users who would recommend it.

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Executive SummaryUpdated on Dec 5, 2024

Dataiku and Amazon SageMaker are two prominent platforms competing in the domain of data science and machine learning. For businesses prioritizing ease of use and collaboration, Dataiku appears to have the advantage. However, for experienced data teams prioritizing scalability and performance, Amazon SageMaker stands out with robust integrations and comprehensive features.

Features: Dataiku is praised for its visual interface that aids in workflow creation and its ability to integrate seamlessly with various data sources. It also supports a range of languages, enhancing its versatility as a user-friendly tool. On the other hand, SageMaker offers advanced machine learning capabilities, coupled with an integrated development environment ideal for code-first approaches. Its automation tools for model tuning contribute to SageMaker's position as a robust solution for complex tasks and deployments.

Room for Improvement: Dataiku could enhance its scalability options for larger enterprises, streamline integration with more cloud services, and provide more advanced automation features. SageMaker could improve by simplifying its deployment processes, offering more intuitive support options, and reducing the complexity of its interface for users less familiar with AWS services.

Ease of Deployment and Customer Service: Dataiku's intuitive deployment process requires little technical expertise, which, combined with responsive customer support, makes it accessible for most businesses. Conversely, while SageMaker offers a more complex deployment model, it allows for extensive customization and scalability, making it ideal for larger operations. The platform benefits from AWS's comprehensive service structure, but it requires experienced users to navigate its full potential.

Pricing and ROI: Dataiku adopts a straightforward pricing model, which tends to result in predictable costs and strong ROI through collaborative efficiency. For SageMaker, the usage-based pricing can cater well to scaling needs but poses a risk of unforeseen expenses. Despite its complexity and learning curve, the advanced features justify the costs for organizations able to maximize its potential, particularly in large-scale environments.

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

Buyer's Guide

Amazon SageMaker vs. Dataiku

December 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of December 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.7%, up from 2.7% compared to the previous year. The mindshare of Amazon SageMaker is 7.5%, down from 10.1% compared to the previous year. The mindshare of Dataiku is 11.8%, up from 7.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Md Masudul Hassan

Agricultural Finance and IT Researcher at Sher-e-Bangla Agricultural University

Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts

I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.

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Natu Lauchande

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

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

SageMaker Studio sounds very interesting. Feature Store and data pipeline features are very interesting. The product is a one-stop shop. It allows people without much engineering knowledge to try out and deploy models in environments similar to the production environments. The tool makes our ML model development a bit more efficient because everything is in one environment. It is easy to manage compared to when things were in different components of AWS. Amazon SageMaker is in AWS, so I need not pay two bills. It is one less system to manage, so it is easier.

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Sabrine Bendimerad

Data Scientist at Electricite De France

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 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."

"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 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."

"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."

"You can quickly build models because it does the work for you."

"It is a modeling tool with helpful automation."

"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."

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

More IBM SPSS Statistics pros

"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."

"The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities."

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

"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."

"SageMaker is a comprehensive platform where I can perform all machine learning activities."

"It's user-friendly for business teams as they can understand many aspects through the AWS interface."

"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."

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 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 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."

"The solution is quite stable."

"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 is the set of visual data preparation tools."

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

More Dataiku pros

Cons

"The solution needs more planning tools and capabilities."

"Technical support needs some improvement, as they do not respond as quickly as we would like."

"The product should provide more ways to import data and export results that are user-friendly for high-level executives."

"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."

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

"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."

"The reports could be better."

"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."

More IBM SPSS Statistics cons

"Improvements are needed in terms of complexity, data security, and access policy integration in Amazon SageMaker."

"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."

"Lacking in some machine learning pipelines."

"Amazon might need to emphasize its capabilities in generative models more effectively."

"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."

"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."

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

"The platform could be more accessible to users with basic coding skills, making it more intuitive and easier for beginners to use comfortably."

More Amazon SageMaker cons

"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."

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

"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."

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

"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."

"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

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

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

"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."

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

"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."

"More affordable training for new staff members."

More IBM SPSS Statistics pricing and cost advice

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

"The pricing is comparable."

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

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."

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

"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."

"The product is expensive."

"Databricks solution is less costly than Amazon SageMaker."

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%

Computer Software Company

University

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?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

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What needs improvement with IBM SPSS Statistics?

IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...

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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...

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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...

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

Pricing is rated as a six, which is slightly more expensive compared to the budget yet adequate for the capabilities ...

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

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 16% of the time

Alteryx vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 12% 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

More IBM SPSS Statistics Competitors

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 10% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

Hugging Face vs Amazon SageMaker

Compared 5% of the time

More Amazon SageMaker Competitors

Databricks vs Dataiku

Compared 37% of the time

KNIME vs Dataiku

Compared 15% 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

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Amazon SageMaker

December 2024

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Buyer's Guide

Dataiku

December 2024

Download Dataiku product report

Also Known As

SPSS Statistics

AWS SageMaker, SageMaker

Dataiku DSS

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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

December 2024

Free Report: Amazon SageMaker vs. Dataiku

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