Databricks vs Dataiku comparison

Databricks and Dataiku are both solutions in the Data Science Platforms category. Databricks is ranked #1 with an average rating of 8.2, while Dataiku is ranked #7 with an average rating of 7.5. Databricks holds a 19.2% mindshare in Data Science Platforms, compared to Dataiku’s 11.8% mindshare. Additionally, 96% of Databricks 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 SummaryUpdated on Oct 8, 2024

Databricks and Dataiku compete in data analytics and machine learning. Databricks holds the upper hand in scalability and integration, whereas Dataiku excels in user satisfaction through ease of use and collaboration.

Features: Databricks is recognized for processing large data sets and handling complex machine learning tasks with its robust performance. Its scalability and integration capabilities make it appealing to users with varied data demands. Dataiku, on the other hand, simplifies data preparation and machine learning workflows with its intuitive tools, enhancing team collaborations and aligning well for projects.

Room for Improvement: Databricks users often seek improved documentation and user guidance, with notable feedback on enhancing user support. Usability aspects are also mentioned for further enhancement. Dataiku users commonly report performance issues when managing large datasets and express the need for improvements in processing speed and capabilities to handle high volume data.

Ease of Deployment and Customer Service: Databricks provides flexible deployment options, though users report varying experiences with customer service. Dataiku is praised for straightforward deployment processes and consistent support, providing a smoother user experience in these areas.

Pricing and ROI: Databricks presents pricing concerns for smaller organizations. Still, users acknowledge solid ROI due to its performance. Dataiku is seen as a more affordable option, offering notable ROI through enhanced collaboration and productivity. This perception makes Dataiku favorable for cost-conscious teams seeking significant investment returns.

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

Buyer's Guide

Databricks 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 Databricks is 19.2%, up from 18.7% 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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Dunstan Matekenya

Data Scientist at a financial services firm with 10,001+ employees

Process large-scale data sets and integrates with Apache Spark with notebook environment

Databricks integrates natively with Apache Spark, which I use as a processing engine for large-scale datasets. This native integration is one of its strengths. Another strength is that the platform makes it very easy to manage resources. For example, setting up a cluster of five or fifteen nodes is straightforward with Databricks. The notebook environment is also excellent, making it easy to perform various tasks.

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

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

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

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

"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."

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

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

"Most of the product features are good but I particularly like the linear regression analysis."

More IBM SPSS Statistics pros

"Its lightweight and fast processing are valuable."

"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."

"The solution is an impressive tool for data migration and integration."

"I work in the data science field and I found Databricks to be very useful."

"The most valuable feature of Databricks is the notebook, data factory, and ease of use."

"The solution is built from Spark and has integration with MLflow, which is important for our use case."

"The most valuable feature is the ability to use SQL directly with Databricks."

"We have the ability to scale, collaborate and do machine learning."

More Databricks pros

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

"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."

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

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

"The solution is quite stable."

More Dataiku pros

Cons

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

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

"Needs more statistical modelling functions."

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

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

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

"The design of the experience can be improved."

"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."

More IBM SPSS Statistics cons

"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."

"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."

"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."

"Doesn't provide a lot of credits or trial options."

"The connectivity with various BI tools could be improved, specifically the performance and real time integration."

"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."

"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."

"I would love an integration in my desktop IDE. For now, I have to code on their webpage."

More Databricks cons

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

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

"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."

"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."

"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."

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

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

More Dataiku cons

Pricing and Cost Advice

"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."

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

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

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

"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."

"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."

More IBM SPSS Statistics pricing and cost advice

"The product pricing is moderate."

"There are different versions."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"Databricks are not costly when compared with other solutions' prices."

"We're charged on what the data throughput is and also what the compute time is."

"Databricks' cost could be improved."

"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

More Databricks 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

16%

Computer Software Company

11%

Manufacturing Company

Healthcare 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...

See all answers

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...

See all answers

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or ...

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

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analyti...

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

Informatica PowerCenter vs Databricks

Compared 8% of the time

Amazon SageMaker vs Databricks

Compared 8% of the time

Dremio vs Databricks

Compared 8% of the time

Microsoft Power BI vs Databricks

Compared 6% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

KNIME vs Dataiku

Compared 15% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 11% of the time

Amazon SageMaker vs Dataiku

Compared 6% 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

Databricks

December 2024

Download Databricks product report

Buyer's Guide

Dataiku

December 2024

Download Dataiku product report

Also Known As

SPSS Statistics

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Dataiku DSS

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IBM

Databricks

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.”

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

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

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

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

Buyer's Guide

Databricks vs. Dataiku

December 2024

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