Try our new research platform with insights from 80,000+ expert users

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
6th
Average Rating
8.4
Reviews Sentiment
6.9
Number of Reviews
85
Ranking in other categories
Predictive Analytics (1st), Data Preparation Tools (1st)
Google Cloud Datalab
Ranking in Data Science Platforms
19th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (16th)
 

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Alteryx is 3.7%, down from 6.5% compared to the previous year. The mindshare of Google Cloud Datalab is 1.6%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Alteryx3.7%
Google Cloud Datalab1.6%
Other94.7%
Data Science Platforms
 

Featured Reviews

Rajneesh Prajapati - PeerSpot reviewer
Senior Rpa Consultant at Accely Consulting
Time-saving workflows have transformed data preparation and predictive analysis for my team
Some of the best features Alteryx offers are its no and low-code capabilities. It delivers massive time-saving and includes spatial and predictive analysis. Alteryx includes built-in tools such as drive time analysis and linear regression, which are much harder to achieve in standard BI tools such as Power BI or Tableau. In addition to these features, Alteryx provides built-in spatial tools that can calculate drive time and location-based insights with minimal effort through drag-and-drop spatial tools, low complex coding, faster, and more accurate results. Linear regression predicts sales based on marketing spend, estimates costs based on usage, and identifies trends in historical data. Alteryx has positively impacted my organization by saving time, improving accuracy, and enabling better decision-making. Using Alteryx, complex tasks such as data cleansing, joining datasets, drive time analysis, and linear regression can be done much faster compared to manual Excel or SQL work. This reduces dependency on manual effort and lowers the risk of human error. Drive time analysis helps my organization make better location-based decisions, such as identifying optimal service areas or improving customer reach.
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

"I like the fact that you can easily blend data from different platforms."
"The filtering is fast, and it provides a search tool that is great."
"The most valuable feature of Alteryx is its performance. It is a powerful solution."
"The initial setup is easy."
"The value add of Alteryx is the agility for making changes, and speed of deployment."
"Alteryx offers a cognitive approach to better understand data and purposes."
"Good data transformation."
"Predictive models, which are easy to use, and help a lot with fast design and deployment​."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"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."
"The APIs are valuable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
 

Cons

"It would be great to create the final users' visualization within Alteryx."
"The data integration component could most likely be improved to increase enterprise scalability."
"The solution is improving continuously. They have, for example, just added automatic insights. If they continue to improve on their overall service offering, that would be ideal."
"There were times when the product would fail during development without an apparent reason."
"Alteryx can improve in data science. They have to have more features and components in the data science aspect because they claim to be a data science tool. However, in order to be more competitive, they have to improve on their data science propositions. Thre are other solutions on the market, such as other players in the market, Data2Go or DataIQ, and Alteryx needs to catch up."
"They should make the solution user-friendly for nontechnical people by giving specific names to the options."
"Even when it already includes some AI models, this area could be improved."
"The tool could include more native connectors, such as for global ERPs, instead of requiring additional fees for these connections."
"The product must be made 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."
"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."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
 

Pricing and Cost Advice

"The seat is too expensive."
"It's probably on the pricey side, but they provide some really useful ways to grow and test."
"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."
"A designer and scheduler for $13K/year in total is pretty much earning you the money back in time and in other resources."
"It's very expensive. I'd rate it a four out of ten in terms of the price. It's great for big companies but not for small companies."
"It has a good price."
"I don't know much about the licensing, but there are some additional costs for certain features."
"ROI is huge. There are some secondary benefits, like analysts getting their post 5 PM time back or the ability to shorten all closing processes to a half or less."
"The product is cheap."
"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."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
884,873 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
21%
Manufacturing Company
9%
Computer Software Company
7%
Retailer
6%
Financial Services Firm
25%
University
9%
Outsourcing Company
7%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business32
Midsize Enterprise15
Large Enterprise54
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 do you like most about Google Cloud Datalab?
Google Cloud Datalab is very customizable.
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 ...
 

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: March 2026.
884,873 professionals have used our research since 2012.