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Dataiku vs Starburst Enterprise comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.0
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Starburst Enterprise
Ranking in Data Science Platforms
14th
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
Streaming Analytics (12th)
 

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 Dataiku is 11.5%, up from 7.5% 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

AbakarAhmat - PeerSpot reviewer
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…
Sabrine Bendimerad - PeerSpot reviewer
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.
KamleshPant - PeerSpot reviewer
Aug 22, 2024
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.

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 software offers consistency across multiple research projects helping us with predictive analytics capabilities."
"It is a modeling tool with helpful automation."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"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."
"It offers very good visualization."
"SPSS is quite robust and quicker in terms of providing you the output."
"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."
"Data Science Studio's data science model is very useful."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"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."
"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."
"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."
"It's very scalable, fast performing, and supports many catalogs."
"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."
 

Cons

"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The technical support should be improved."
"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"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."
"Better documentation on how to use macros."
"IBM SPSS Statistics does not keep you close to your data like KNIME."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"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."
"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)."
"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."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"I think it would help if Data Science Studio added some more features and improved the data model."
"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."
"The ability to have charts right from the explorer would be an improvement."
"There should be support for REST API data sources to access data from the web."
"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."
 

Pricing and Cost Advice

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"We think that IBM SPSS is expensive for this function."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"More affordable training for new staff members."
"I rate the tool's pricing a five out of ten."
"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."
"Pricing is pretty steep. Dataiku is also not that cheap."
"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."
"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
17%
University
9%
Computer Software Company
9%
Manufacturing Company
8%
Financial Services Firm
18%
Educational Organization
16%
Manufacturing Company
9%
Computer Software Company
8%
Financial Services Firm
44%
Computer Software Company
10%
Energy/Utilities Company
4%
Government
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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.
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...
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.
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...
What is your primary use case for Dataiku Data Science Studio?
We use the solution for data science and machine learning.
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...
What needs improvement with Starburst Enterprise?
There are no specific projects supported by Starburst regarding AI initiatives or machine learning projects. In the f...
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 ...
 

Also Known As

SPSS Statistics
Dataiku DSS
No data available
 

Learn More

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Overview

 

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
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
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Find out what your peers are saying about Dataiku vs. Starburst Enterprise and other solutions. Updated: October 2024.
815,854 professionals have used our research since 2012.