Dataiku vs Starburst Enterprise comparison

Dataiku and Starburst are both solutions in the Data Science Platforms category. Dataiku is ranked #7 with an average rating of 7.8, while Starburst is ranked #14 with an average rating of 8.5. Dataiku holds a 12.4% mindshare in Data Science Platforms, compared to Starburst’s 2.1% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 100% of Starburst users who would recommend it.

Dataiku

Read 10 Dataiku reviews

7,100 Views
5,859 Comparison Views

100% willing to recommend

Starburst Enterprise

Read 2 Starburst Enterprise reviews

1,242 Views
1,083 Comparison Views

100% willing to recommend

Dataiku

Starburst Enterprise

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Dataiku and Starburst Enterprise are competing analytics platforms in the data handling category. While Dataiku leads with user-friendly features and machine learning, Starburst Enterprise stands out in scalability and advanced querying.

Features: Dataiku offers user-friendly data prep, intuitive machine learning model building, and a platform suitable for non-technical practitioners. Starburst Enterprise provides robust federated querying, seamless access across data sources, and powerful querying features for diverse data environments.

Ease of Deployment and Customer Service: Dataiku supports cloud-based deployment suitable for collaborative environments and provides responsive support with comprehensive documentation. Starburst Enterprise focuses on deployment for complex query optimization, appealing to technical organizations with large infrastructures.

Pricing and ROI: Dataiku aligns its setup costs with the promise of high ROI through scalable and agile solutions. Starburst Enterprise incurs higher implementation expenses but justifies them with enhanced querying performance and efficiency, offering significant ROI for enterprises needing extensive data connectivity.

To learn more, read our detailed Dataiku vs. Starburst Enterprise Report (Updated: January 2025).

Buyer's Guide

Dataiku vs. Starburst Enterprise

January 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Dataiku

Ranking in Data Science Platforms

7th

Average Rating

8.0

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Starburst Enterprise

Ranking in Data Science Platforms

14th

Average Rating

8.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Streaming Analytics (12th)

Mindshare comparison

As of February 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.4%, up from 7.9% compared to the previous year. The mindshare of Starburst Enterprise is 2.1%, up from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

RichardXu

Data Science Lead at a mining and metals company with 10,001+ employees

The platform organizes workflows visually and efficiently

One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.

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KamleshPant

Senior Software Architect at USEReady

Connects to any data source from any region and offers unified access

There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the future, if we have all the data available, we can definitely capitalize on AI/ML and LLM capabilities to summarize data and gain insights. That's our future goal, but we haven't reached that point yet. There should be support for REST API data sources to access data from the web. We often have data coming in and communicate with data sources via REST API calls. I don't see that capability in Starburst currently; everything is through JDBC or ODBC. If Starburst could seamlessly access data using REST API capabilities, it would be a game-changer. The self-service data management features, like self-service materialized views, are great, but they can be a bit complex for basic users to understand.

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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 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 is the set of visual data preparation tools."

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

"I rate the overall product as eight out of ten."

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."

"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."

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

More Dataiku pros

"We have noticed improvements in performance using Starburst Enterprise. It handles complex data, including reading and partitioning files. We can add a new catalog to Starburst Enterprise by providing connection details and service account information. This allows us to integrate with existing tools, such as the Snowflake database, which we use for data protection in our project."

"It's very scalable, fast performing, and supports many catalogs."

Cons

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

"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."

"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 area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."

"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."

"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

"Starburst Enterprise could improve by offering additional features similar to those provided by other SQL query tools. For example, incorporating functionalities like pivot tables would make it more feasible to use."

"There should be support for REST API data sources to access data from the web."

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."

"I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of using Starburst Enterprise can vary based on the amount of data you're processing and the type of machines you opt for, whether on AWS or another cloud platform."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Educational Organization

15%

Manufacturing Company

Computer Software Company

Financial Services Firm

45%

Computer Software Company

10%

Energy/Utilities Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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

There are no extra expenses beyond the existing licensing cost.

See all answers

What needs improvement with Dataiku Data Science Studio?

I need more experience in the sector, which is health. The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience.

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

I use that IQ since I am preparing cohorts for health investment research.

See all answers

What is your experience regarding pricing and costs for Starburst Enterprise?

I haven't personally dealt with the pricing aspects first-hand, but from what I understand, it largely depends on the specifics of your setup, especially the machines you use on AWS. The cost of us...

See all answers

What needs improvement with Starburst Enterprise?

See all answers

What is your primary use case for Starburst Enterprise?

We use Starburst with one client who is exploring their ecosystem to remove data silos and enable data access across departments. It's a very big ecosystem, like a finance institute. They are curre...

See all answers

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Compared 20% of the time

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Compared 18% of the time

Alteryx vs Starburst Enterprise

Compared 11% of the time

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Product Reports

Buyer's Guide

Dataiku

February 2025

Download Dataiku product report

Buyer's Guide

Data Science Platforms

January 2025

Download Starburst Enterprise product report

Also Known As

Dataiku DSS

No data available

Overview

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.

Dataiku

Starburst Enterprise is a data analytics platform that enables organizations to access and analyze data from multiple sources, including cloud-based and on-premises data warehouses. It provides a single access point to all data sources, allowing users to query and analyze data without moving it between systems.

By providing a unified view, Starburst Enterprise helps organizations make better-informed decisions and improve operational efficiency, leading to better customer insights and more accurate forecasting. Overall, Starburst Enterprise is a powerful tool for organizations looking to unlock the full potential of their data.

Starburst

Sample Customers

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

Information Not Available

Buyer's Guide

Dataiku vs. Starburst Enterprise

January 2025

Free Report: Dataiku vs. Starburst Enterprise

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