No more typing reviews! Try our Samantha, our new voice AI agent.

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
18th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (16th)
 

Mindshare comparison

As of June 2026, in the Data Science Platforms category, the mindshare of Alteryx is 3.7%, down from 6.1% 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

"Once we got it in-house, I knew its value."
"Alteryx is easier to set up and implement and allowed us to also focus on different aspects of the business."
"One-stop shop for data preparation, blending, prediction, and optimization in a single workflow."
"We are taking the data from disparate systems and transforming and making the data available for further visualization."
"Alteryx effectively visualizes the flow of data and what happens at each stage. I also like that it's a no-code solution. I also like that you can troubleshoot certain parts of the workflow by putting them in a sandbox."
"The cloud deployment ensures it scales easily."
"Alteryx is very good; you can do literally anything on Alteryx, it is so advanced, and it's just drag and drop, so you don't need to know any coding or other technical stuff to use it."
"Alteryx speeds up the time to obtain business answers/insights on data."
"The APIs are valuable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"For me, it has been a stable product."
 

Cons

"The desktop license is expensive."
"Visualization: There is room to improve here."
"The solution can be made more affordable."
"Even when it already includes some AI models, this area could be improved."
"The server is too expensive for what you get and it is really a designer desktop on a server. It is not worth the money."
"There were times when the product would fail during development without an apparent reason."
"We can't browse multiple files. When we deploy a solution on a gallery, let's say I have ten different files, and I have to upload them all at once. This is something that's difficult in the gallery. So case by case, I see some downsides, but often we do something alternative."
"There's a big jump in terms of pricing between license tiers. I'm not sure I understand why the price jumps are so high."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"The interface should be more user-friendly."
"The product must be made more user-friendly."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"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."
"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 cost of the solution could be reduced."
"The license is really expensive, we cannot afford to have two or three. It takes away all the budget of my area."
"Alteryx isn't extortionately expensive, but it's not cheap either."
"It is an expensive solution."
"We have a yearly cost that we pay for the licensing. We do not pay any costs in addition to the licensing fees."
"Alteryx is generally more suited for medium—to large companies due to its potentially high licensing costs."
"The solution has a more costly license than other tools in the market."
"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."
"It is affordable for us because we have a limited number of users."
"The pricing is quite reasonable, and I would give it a rating of four out of ten."
"The product is cheap."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
899,917 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
19%
Manufacturing Company
8%
Computer Software Company
7%
Construction Company
6%
Financial Services Firm
19%
Construction Company
18%
University
7%
Outsourcing Company
6%
 

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...
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...
 

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.
899,917 professionals have used our research since 2012.