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Alteryx vs Google Cloud Datalab comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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

Alteryx
Ranking in Data Science Platforms
4th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
87
Ranking in other categories
Predictive Analytics (1st), Data Preparation Tools (1st)
Google Cloud Datalab
Ranking in Data Science Platforms
22nd
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (26th)
 

Mindshare comparison

As of August 2026, in the Data Science Platforms category, the mindshare of Alteryx is 3.7%, down from 6.0% compared to the previous year. The mindshare of Google Cloud Datalab is 1.7%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Alteryx3.7%
Google Cloud Datalab1.7%
Other94.6%
Data Science Platforms
 

Featured Reviews

ManojBehera - PeerSpot reviewer
Senior Staff Cyber Security Cloud Data Architect at GE Healthcare
Automated complex ETL workflows have reduced coding effort and improved data integration
One area for improvement is in integrating mostly the data which comes from telemetry, where I can see some sort of improvisations can be made. It is a massive amount of unstructured data, and I believe Alteryx is able to handle it, but there can be some improvements. Suggestions for improvements in Alteryx include areas for increasing efficiency, particularly in processing telemetry data, which involves dealing with large volumes of unstructured data. Additionally, I believe when we use filter tools immediately after the input source, there can be slowdowns when handling massive data. The user experience of Alteryx is generally good, but there are areas for improvement from a user's perspective, particularly regarding user interface enhancements. I think there's always room for improvement, but otherwise, Alteryx has been a great tool for me. We haven't experienced significant disruptions while increasing data volumes, though I sense there could be performance issues as data grows exponentially. This is an area that could use improvement in Alteryx.
LJ
System Architect at UST Global España
dashboards are good and data visualization is more meaningful for the end-user
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcing your database with over a billion records, it can be tough for the end-user to manage the data. You need to have a single entity system in each environment. It's not because of GCP, but it would be great to have options like MongoDB or other similar tools in GCP. Then, we wouldn't always need to connect to the cloud and execute SQL queries. Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated. Once the data is collected, it should be easily sorted.

Quotes from Members

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

Pros

"The connectors are a very good feature."
"The solution has excellent drag and drop functionality, there's no need for coding, and there are nodes ready for us to use as well, which makes everything extremely easy and the user-friendliness a big draw for us."
"I believe that the ability to leverage the gallery for scalability, as well as the general data blending functionality, is most beneficial to our core-based users."
"Our analyst’s time was cut from two days to one hour of data blending and the output was amazing!"
"The connection feature is quite useful to our organization; we connect with Microsoft SQL databases, Oracle databases, SharePoint lists, and Outlook email servers, and the stability and scalability have been very good with no issues."
"The solution has a very strong community that is involved in the product. It helps make the usage easier and helps us find answers to our questions."
"The analytics are easy​."
"Predictive models, which are easy to use, and help a lot with fast design and deployment​."
"For me, it has been a stable product."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
 

Cons

"The workflow and pipeline need to improve."
"It would be nice if they can provide Alteryx with more options for In-DB connectivity. That functionality is there, but it doesn't include all software we are connecting."
"Alteryx's predictive data models are pretty average and can be improved."
"They can provide some pre-built tools for predictive analytics instead of us having to build all the tools. It should also be improved from the visualization aspect. It should have better visualization capabilities. There are tools out there that have better visualization capabilities, which Alteryx is lacking currently."
"I mostly used it for flat files, but I have many colleagues who reported that to tune a query, in case they want to directly connect to the database, there is no option to optimize the performance of the query, as we have in Informatica."
"All of the reports are migrated or exported in an Excel file, and most of the time, a business intelligence tool is required. They could have better reporting. The aesthetic could be improved."
"I'd like it to be easier to work with PDF."
"The software is not fully optimized."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"The product must be made more user-friendly."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The interface should be more user-friendly."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
 

Pricing and Cost Advice

"The designer has a list price of $5,995 USD."
"My organization pays for it, and I do not look into the financial aspect of the licensing, but I know it is pretty expensive."
"Its price should be lower. The key thing that we see is that talking about ROI is an important element at the time of purchase. Cost becomes a factor in every discussion. Justifying the ROI for these kinds of workflows is always a challenge, and the only way to counter the challenge is by addressing the pricing."
"In order to have designers, and, if you want to collaborate, you have to buy a server. If the designer is $5,000, and if you want a server, you have to pay $80,000."
"The pricing is $5000 per year per production license."
"I don't know much about the licensing, but there are some additional costs for certain features."
"While it offers extensive features, including predictive analytics, for those who mainly use it for data preparation and blending, the cost can be prohibitive."
"The license price of the solution is expensive."
"The pricing is quite reasonable, and I would give it a rating of four out of ten."
"It is affordable for us because we have a limited number of users."
"The product is cheap."
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Manufacturing Company
8%
Construction Company
7%
Computer Software Company
6%
Construction Company
20%
Financial Services Firm
13%
Outsourcing Company
9%
University
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business33
Midsize Enterprise16
Large Enterprise56
No data available
 

Questions from the Community

What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
One of the differences is that with Alteryx you can use it as an ETL and analytics tool. Please connect with me directly if you want to know more.
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
Alteryx is an extremely easy and flexible data tool, flexible in terms of drag and drop toolset and also has python, R integrations if your team requires this. It can handle over 2 billion rows of...
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
I am not familiar with IBM SPSS Modeler, therefore, I cannot compare these two products. Regarding Alteryx I can say the following: - An excellent desktop tool for Data Prep and analytics. - Featu...
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Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
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Find out what your peers are saying about Alteryx vs. Google Cloud Datalab and other solutions. Updated: June 2026.
908,800 professionals have used our research since 2012.