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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
5th
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
16th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (15th)
 

Mindshare comparison

As of May 2026, in the Data Science Platforms category, the mindshare of Alteryx is 3.8%, down from 6.1% compared to the previous year. The mindshare of Google Cloud Datalab is 1.8%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Alteryx3.8%
Google Cloud Datalab1.8%
Other94.4%
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

"Alteryx's connectivity is essential, and we like the ability to connect the solution to multiple sources because it's easier than other data modeling and extraction solutions and is built on a self-service concept, so it's easy for anyone to open the tool and directly import or export data from it."
"After the implementation of Alteryx, the turnaround time has been reduced to 10 minutes or maybe in some cases, a couple of minutes."
"The solution has excellent drag and drop functionality. There's no need for coding."
"The value add of Alteryx is the agility for making changes, and speed of deployment."
"Alteryx significantly reduces the time spent searching for specific information."
"The design portion of this tool is easy to use without code, which his something that something we can appreciate."
"The philosophy of the citizen data scientist is the key piece, which means the no-code analytics capability. This is the feature that attracted us the most."
"The scheduling feature for the automation is excellent."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"All of the features of this product are quite good."
"The APIs are valuable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"For me, it has been a stable product."
"Google Cloud Datalab is very customizable."
"All of the features of this product are quite good."
 

Cons

"It's a technical product and those that don't have proper training will have to deal with a steep learning curve."
"A feature which allows the user to be able to click on an output (in a file browser) and see the creation of the module would be fantastic."
"The desktop license is expensive."
"I'd like it to be easier to work with PDF."
"It is expensive to buy additional licensing, and it is time and resource consuming to install onto our own hardware — which itself requires maintenance and administrative attention."
"The only weakness I would say is on the visualization side of having that dynamic incapability."
"When the workflows are huge and complex, it may take some time to refresh it."
"Even when it already includes some AI models, this area could be improved."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"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."
"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."
"The interface should be more user-friendly."
"The interface should be more user-friendly."
"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."
 

Pricing and Cost Advice

"There are some implementation services and internal effort costs at the beginning but there is nothing else."
"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 seat is too expensive."
"The price for Alteryx Designer is reasonable but the price for Alteryx Server for universal collaborations is too expensive."
"The license price of the solution is expensive."
"Opt for the three year subscription. It is 20% less than the yearly one."
"A designer and scheduler for $13K/year in total is pretty much earning you the money back in time and in other resources."
"We have a yearly cost that we pay for the licensing. We do not pay any costs in addition to the licensing fees."
"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%
Computer Software Company
7%
Retailer
5%
Financial Services Firm
20%
Construction Company
16%
University
7%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business33
Midsize Enterprise16
Large Enterprise57
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...
What needs improvement with Google Cloud Datalab?
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 forcin...
What is your primary use case for Google Cloud Datalab?
It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten servers or systems. Some of them use a mobile network, some are ONTAP networks, and ...
What advice do you have for others considering Google Cloud Datalab?
Overall, I would rate it a nine out of ten. Google Cloud is very good. Once you go through the features of Google Cloud, it's a good idea to get a GCP certification so you have an idea of how it ca...
 

Comparisons

 

Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
Information Not Available
Find out what your peers are saying about Alteryx vs. Google Cloud Datalab and other solutions. Updated: April 2026.
896,387 professionals have used our research since 2012.