Alteryx vs Google Cloud Datalab comparison

Alteryx and Google are both solutions in the Data Science Platforms category. Alteryx is ranked #5 with an average rating of 8.2, while Google is ranked #16 with an average rating of 9.0. Alteryx holds a 3.8% mindshare in Data Science Platforms, compared to Google’s 1.8% mindshare. Additionally, 89% of Alteryx users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

Alteryx

Read 85 Alteryx reviews

8,338 Views
4,669 Comparison Views

89% willing to recommend

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

1,794 Views
1,130 Comparison Views

80% willing to recommend

Alteryx

Google Cloud Datalab

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

Alteryx and Google Cloud Datalab both compete in the data analytics and machine learning market. Alteryx has an edge in user satisfaction and ease of use, while Google Cloud Datalab is favored for its scalability and integration with cloud services.

Features: Alteryx provides advanced analytics without requiring programming, including data preparation, predictive analytics, and seamless integration with Tableau. Its drag-and-drop interface simplifies complex workflows. Google Cloud Datalab offers extensive machine learning features, strong integration with the Google Cloud ecosystem, and robust Python support, allowing for deep customization and automation capabilities.

Room for Improvement: Alteryx could enhance real-time data processing capabilities and expand language support for non-English speaking users. Improved scalability for larger datasets and better cost transparency would also be beneficial. Google Cloud Datalab could work on simplifying the initial setup process, improve user interface intuitiveness for new users, and enhance support and documentation for complex data configurations.

Ease of Deployment and Customer Service: Alteryx offers an intuitive deployment model with strong customer support, making it easy for users to implement and utilize its features. Google Cloud Datalab, as part of the Google Cloud Platform, benefits from a strong cloud infrastructure but requires familiarity with cloud-based systems, which can lead to a steeper learning curve.

Pricing and ROI: Alteryx uses a premium pricing model, justified by its ease of use and fast deployment, leading to a quicker ROI. Google Cloud Datalab's pricing is more flexible, tied to actual usage of Google Cloud services, which may potentially lower costs but necessitates careful management to optimize ROI.

To learn more, read our detailed Alteryx vs. Google Cloud Datalab Report (Updated: April 2026).

Buyer's Guide

Alteryx vs. Google Cloud Datalab

April 2026

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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

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

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
Product	Mindshare (%)
Alteryx	3.8%
Google Cloud Datalab	1.8%
Other	94.4%

Data Science Platforms

Featured Reviews

reviewer2797908

Senior Rpa Consultant at a computer software company with 51-200 employees

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.

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LijomonJose

System Architect at UST Global EspaÃ±a

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.

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Quotes from Members

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

Pros

"It saves time on a lot projects."

"The filtering is fast, and it provides a search tool that is great."

"The most valuable feature of Alteryx is the intelligence suite."

"You don't have to be tech-savvy or technical to use the solution."

"The Alteryx designer has been the most useful feature in the solution."

"It is a very user-friendly product that doesn’t require a strong technical background; you can build something within an hour."

"Alteryx has made us more agile and increased the speed and effectiveness of decision making."

"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."

More Alteryx pros

"The APIs are valuable."

"All of the features of this product are quite good."

"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."

"Google Cloud Datalab is very customizable."

"For me, it has been a stable product."

Cons

"Deep learning models are not currently supported."

"The price for Alteryx Designer is reasonable but the price of the Alteryx Server for universal collaborations is too expensive."

"Alteryx could be improved in the area of analytics and central governance."

"A colleague of mind mentioned that the solution should have more options for the visualization of data."

"There are a few hiccups with specific data sets and languages or formats that the data comes in. That may be a minor problem, but we can work through it. We had some issues looking at XML format in added data, but it wasn't significant."

"Although I use this product regularly, I used to code for many years and I am not a big fan of tools like Alteryx. I don't think that it's a good product, and the reason is that when the use cases get more complex, the models get exponentially larger and more complex to put together."

"Alteryx needs to focus on the supply chain aspect since detecting financial figures and data anomalies is currently insufficient."

"They should work on its pricing."

More Alteryx cons

"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."

"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."

"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

"While it offers extensive features, including predictive analytics, for those who mainly use it for data preparation and blending, the cost can be prohibitive."

"Alteryx isn't extortionately expensive, but it's not cheap either."

"We have a yearly cost that we pay for the licensing. We do not pay any costs in addition to the licensing fees."

"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."

"Opt for the three year subscription. It is 20% less than the yearly one."

"The license is really expensive, we cannot afford to have two or three. It takes away all the budget of my area."

"The desktop platform costs $5,000 per year. It's very costly."

"The cost of the solution could be reduced."

More Alteryx pricing and cost advice

"The product is cheap."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Manufacturing Company

Computer Software Company

Retailer

Financial Services Firm

22%

Construction Company

16%

Comms Service Provider

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	32
Midsize Enterprise	16
Large Enterprise	55

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.

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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...

See all answers

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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What needs improvement with Google Cloud Datalab?

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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 ...

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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...

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Compared 7% of the time

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Product Reports

Buyer's Guide

Alteryx

May 2026

Download Alteryx product report

Buyer's Guide

Google Cloud Datalab

May 2026

Download Google Cloud Datalab product report

Overview

Alteryx provides user-friendly, no-code tools for data blending, preparation, and analysis. Its drag-and-drop interface and in-database capabilities simplify integration with data sources while maintaining data integrity.

Alteryx offers a comprehensive suite for automation of data workflows, reducing manual tasks and enhancing processing efficiency. Known for robust predictive and spatial analytics, it effectively handles large datasets. The platform's flexibility allows for custom script deployments, supported by a strong community. However, Alteryx faces challenges with high pricing, lack of cloud support, and limited data visualization tools. Users express a need for more in-built data science functionalities, improved API integration, and a smoother learning curve. Connectivity and documentation gaps, along with complex workflows, are noted concerns, suggesting areas for enhancement. Alteryx is widely used for tasks like ETL processes, data preparation, predictive modeling, and report generation, supporting functions like financial projections and spatial analysis.

What features define Alteryx?

Data Blending: Combines data from multiple sources.
No-Code Tools: User-friendly drag-and-drop interface for ease of use.
Automation: Streamlines workflows and reduces manual tasks.
Predictive Analytics: Offers advanced forecasting capabilities.
Spatial Analytics: Processes geospatial data effectively.

What benefits should users consider?

Reduced Manual Labor: Automation minimizes repetitive tasks.
Data Integration: Seamlessly connects to various data sources.
Customization: Flexibility to deploy custom scripts.
Scalability: Quickly processes large datasets.
Community Support: Strong network for troubleshooting and guidance.

Alteryx is implemented across industries for diverse needs such as anomaly detection in finance, customer segmentation in marketing, and tax automation in auditing. Teams leverage its capabilities for data blending and predictive modeling to enhance operational efficiency and address specific business needs effectively.

Alteryx

Google Cloud Datalab offers an integrated environment for seamless data processing and analysis. It combines robust infrastructure with free call-up features to enhance user experience, making it a go-to choice for data-driven tasks.

Google Cloud Datalab is geared towards users seeking efficient data handling solutions. It provides a seamless setup with robust infrastructure, focusing on enhancing APIs and offering meaningful data visualization through its dashboards. Notable AI capabilities include auto-completion and data logging, although some minor configuration challenges exist. While transitioning from AWS can be complex, the platform supports dynamic data pipeline design that suits Python development, offering an end-user friendly environment.

What are the key features of Google Cloud Datalab?

Robust Infrastructure: Provides seamless setup with strong backend support.
Free Call-Up: Allows use without extra costs, enhancing accessibility.
Data Visualization: Dashboards offer meaningful insights into data trends.
AI Capabilities: Features auto-completion and data logging for efficiency.
Customizable Architecture: Adapts to different data handling needs effectively.

What benefits should users expect from Google Cloud Datalab?

Efficient Data Analysis: Streamlines exploratory data analysis in machine learning.
Enhanced API Value: API integrations add significant value to data handling.
Friendly Python Environment: Suitable for end-users looking for ease in Python development.
Adaptive Pipeline Design: Supports complex data transitions from AWS.
Global Availability: Helps overcome time lag issues with server location selection.

In specific industries, Google Cloud Datalab is instrumental in managing data analysis, machine learning exploration, and dataset preprocessing. It facilitates the transfer of workloads from AWS and ensures efficient daily data processing. Organizations benefit from its capability to provision machine learning models into Vertex AI, bolstering research and development efforts. The global availability feature plays a significant role in selecting optimal server locations, addressing time lag and connectivity challenges.

Google

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen

Information Not Available

Buyer's Guide

Alteryx vs. Google Cloud Datalab

April 2026

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