Google Cloud Datalab vs Qlik Sense comparison

Google and Qlik are both solutions in the Data Visualization category. Google is ranked #26, while Qlik is ranked #6 with an average rating of 7.9. Google holds a 1.2% mindshare in DV, compared to Qlik’s 4.9% mindshare. Additionally, 80% of Google users are willing to recommend the solution, compared to 96% of Qlik users who would recommend it.

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

2,400 Views
1,008 Comparison Views

80% willing to recommend

Qlik Sense

Read 126 Qlik Sense reviews

11,947 Views
6,690 Comparison Views

96% willing to recommend

Google Cloud Datalab

Qlik Sense

Comparison Buyer's Guide

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Executive SummaryUpdated on Jan 1, 2025

Qlik Sense and Google Cloud Datalab both operate in the data analytics space. Qlik Sense is preferred for its pricing and customer support, while Google Cloud Datalab stands out with its comprehensive features.

Features: Qlik Sense offers powerful data visualization, a user-friendly interface, and rapid development capabilities. It uses an associative engine, allowing for efficient data exploration without predefined paths. Google Cloud Datalab provides robust data exploration tools, collaborative features tailored for data scientists, and the ability to handle large datasets efficiently, supported by Google Cloud's infrastructure.

Room for Improvement: Qlik Sense could enhance its customization options, improve scalability for large enterprises, and offer better handling of real-time data. Google Cloud Datalab might benefit from simplifying its user interface, improving the integration with non-Google services, and reducing the complexity of technical setup.

Ease of Deployment and Customer Service: Qlik Sense offers a straightforward deployment process with comprehensive customer support, making it suitable for businesses that need quick and easy solutions. Conversely, Google Cloud Datalab's deployment process, integrated within Google Cloud Platform, requires more technical expertise but offers a wide range of cloud capabilities and extensive online resources for support.

Pricing and ROI: Qlik Sense provides flexible and often cost-effective pricing models, resulting in a good return on investment for companies focusing on data visualization without extensive technical requirements. Meanwhile, Google Cloud Datalab involves higher initial setup costs due to its integration with Google Cloud services, but it can offer significant value for organizations focusing on comprehensive data analysis and machine learning solutions.

To learn more, read our detailed Google Cloud Datalab vs. Qlik Sense Report (Updated: June 2026).

Buyer's Guide

Google Cloud Datalab vs. Qlik Sense

June 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

Google Cloud Datalab

Ranking in Data Visualization

26th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Science Platforms (22nd)

Qlik Sense

Ranking in Data Visualization

6th

Average Rating

8.6

Reviews Sentiment

6.2

Number of Reviews

126

Ranking in other categories

Embedded BI (2nd), AI Data Analysis (16th)

Mindshare comparison

As of August 2026, in the Data Visualization category, the mindshare of Google Cloud Datalab is 1.2%, up from 0.7% compared to the previous year. The mindshare of Qlik Sense is 4.9%, down from 8.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Visualization Mindshare Distribution
Product	Mindshare (%)
Qlik Sense	4.9%
Google Cloud Datalab	1.2%
Other	93.9%

Data Visualization

Featured Reviews

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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Saranya Deepthi

Project Engineer at Wipro

Improved AI-driven dashboards have accelerated decisions but still need better visuals and faster refresh

Absolutely, nothing is entirely positive, and everything has both advantages and disadvantages. When I worked with Qlik Sense, circular charts were not available, which meant I had to look for alternative solutions that would be reliable or make the functionality work. There are some features that need to be added. Additionally, there is a limit to the number of fields that can be added in Qlik Sense, and I believe it would be beneficial if they increased the count for fields and columns. There might be requirements where an Excel file contains many columns that need to be displayed as visual representations to clients, and in those situations, it becomes very difficult and I have to use alternative approaches. When this problem arose, I used HTML code to write a solution and make it work. Qlik Sense should avoid these types of limitations in future updates. Another issue is page resolution. If a client wants to view the dashboard on a single page without scrolling, bar charts appear small and the values in KPIs, bar charts, scatter plots, and line graphs cannot be seen very clearly. Adding more extensions to make the job easier would also be beneficial. Improvements to reporting would be helpful as well, because working with large datasets makes reporting very difficult. Additionally, when data is refreshed, it cannot be completed in a short timeframe. Refreshing very large datasets can take one, two, or even three hours, so reducing the refresh time would be very useful for customers.

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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

"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."

"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."

"The APIs are valuable."

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

"We were able to identify easy things, such as when a contract was loaded incorrectly."

"Lots of end-users are now familiar enough with this solution to create quick dashboards based on their own data sources, like Excel files, CSV, TXT files, and databases."

"There are a lot of features available in this solution, it has been very easy to use. We have found it to be less complex and user-friendly compared to other solutions we have used."

"The most valuable feature is the user experience."

"On the fly questions can be answered with the "Qlik" of a button and drive forward discussions about policy, mission, and goals."

"This tool not only allows for consumption of the data in a visual way, but also allows the user to modify the question to get new answers."

"Unique data visualizations created based on - among others - customer reviews and hands-on experience. Qlik is an experienced company in the Business Intelligence / Data visualization area, that doesn't necessarily mean it is the best solution, however, based on my personal experience it is much more complex than Power BI and Tableau as I've had some things to do with these two concurrent softwares."

"I am very happy with Qlik and the solutions they offer, as it allows for great flexibility and ease of use."

More Qlik Sense pros

Cons

"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."

"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."

"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."

"My advice to others is to make sure they have a good technical team. We have found that a lot of the consultants go in and out of the business and sometimes you are left alone without assistance."

"Making it as user friendly as possible"

"The solution needs to make improvements to the licensing model. They need to make it more affordable at scale, and to make it more affordable for those companies at the low end of the market as well."

"Being able to share and modifying on the fly can be improved."

"They need much better server management. Currently, even a single application can crash the whole server."

"Only when our usage outgrew our physical environment (server size) did we have stability issues."

"The cost of the Qlik ecosystem is higher than other competitors."

"Even though the solution is a self-service solution, many non-technical users still struggle to create their reports."

More Qlik Sense cons

Pricing and Cost Advice

"The pricing is quite reasonable, and I would give it a rating of four out of ten."

"The product is cheap."

"It is affordable for us because we have a limited number of users."

"Licensing could be cheaper."

"QlikSense offers a Hybrid environment architecture, which is very cost effective based on where the enterprise data resides."

"The costs can initially become quite high. Make sure you have a clear understanding of who will truly use the product as opposed to someone that will simply receive the end report."

"Start small with tokens. You can always buy more."

"Know your needs when going into the purchasing decision."

"It is a little expensive for the Italian market. Normally, Qlik Sense has two types and costs. The medium cost is around 700 euros per year."

"Licensing: Review the named model and move towards a usage model (e.g., cores, memory, computers, API calls, etc.)."

"You will spend more time on educating your staff than licensing the product."

More Qlik Sense pricing and cost advice

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Top Industries

By visitors reading reviews

Construction Company

20%

Financial Services Firm

13%

Outsourcing Company

University

Financial Services Firm

18%

Construction Company

Manufacturing Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	34
Midsize Enterprise	40
Large Enterprise	89

Questions from the Community

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Seeking lightweight open source BI software

It depends on the Data architecture and the complexity of your requirement. Some great tools in the market are Qlik Sense, Power BI, OBIEE, Tableau, etc. I have recently started using Cognos Enter...

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Seeking lightweight open source BI software

There are many...It would rather depend what System BI architecture or Enterprise legacy you have at your end...I would recommend as follows: 1) If you have legacies of SAP, Oracle - look for SAP...

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What is your experience regarding pricing and costs for Qlik Sense?

It is not about performance. It is just about how expensive it is to implement.

See all answers

Comparisons

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Compared 7% of the time

Anaconda Business vs Google Cloud Datalab

Compared 6% of the time

JungleWorks Kato vs Google Cloud Datalab

Compared 5% of the time

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Tableau Enterprise vs Qlik Sense

Compared 6% of the time

Apache Superset vs Qlik Sense

Compared 5% of the time

Microsoft Power BI vs Qlik Sense

Compared 4% of the time

OpenText Intelligence vs Qlik Sense

Compared 4% of the time

SAP BusinessObjects Business Intelligence vs Qlik Sense

Compared 3% of the time

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Product Reports

Buyer's Guide

Google Cloud Datalab

July 2026

Download Google Cloud Datalab product report

Buyer's Guide

Qlik Sense

July 2026

Download Qlik Sense product report

Also Known As

No data available

QlikSense, Qlik Analytics Platform

Overview

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

Qlik Sense offers drag-and-drop dashboard creation, multi-data source integration, and self-service analytics. Users benefit from associative data modeling and real-time insights. The platform enhances quick deployment across any device with its flexibility and ease of use.

Qlik Sense provides rapid dashboard creation and seamless multi-data source integration, supporting real-time analytics and high-speed ETL capabilities. Users enjoy advanced visualizations and natural language processing within an intuitive interface. The solution's in-memory engine ensures fast data processing while offering flexibility and quick deployment on all devices. Its open API facilitates extensive customization and integration with chatbots and third-party extensions.

What are the key features of Qlik Sense?

Rapid Dashboard Creation: Enables quick creation of insightful dashboards using a drag-and-drop interface.
Multi-Data Source Integration: Supports seamless integration across various data sources for comprehensive analysis.
Self-Service Analytics: Empowers users with intuitive tools for independent data exploration and insights generation.
Associative Data Modeling: Enhances understanding of complex datasets and relationships.
Advanced Visualizations: Offers sophisticated visual options to present data clearly and engagingly.
Real-Time Insights: Provides up-to-the-minute data analysis capabilities.
Open API Integration: Allows extensive customization and integration with third-party tools.

What benefits should users look for in reviews?

Fast Deployment: Enjoys rapid setup and integration across devices, facilitating immediate data access.
Enhanced Flexibility: Customization options allow tailored solutions that meet specific user needs.
Comprehensive Integration: Capable of integrating multiple data sources, improving analytical scope.
Improved Data Accessibility: Offers easy access and understanding of complex data.
Automation Efficiency: Streamlines reporting and analytics tasks, boosting productivity.

In industries such as finance and sales, Qlik Sense enables interactive data analyses and dashboard creation across departments. It supports business intelligence for financial reporting, sales analysis, and decision-making. By automating reporting and combining data from multiple sources, it facilitates users in generating insights and enhancing data accessibility for informed business decisions.

Qlik

Sample Customers

Information Not Available

Abbvie, Airbus, Barclays, BT Openreach, BMW, Daimler AG, HSBC, IKEA, Nationwide Building Society, Royal Mail Group, Sanofi, Siemens, Wendy'', Vodafone, Volvo

Buyer's Guide

Google Cloud Datalab vs. Qlik Sense

June 2026

Free Report: Google Cloud Datalab vs. Qlik Sense

Find out what your peers are saying about Google Cloud Datalab vs. Qlik Sense and other solutions. Updated: June 2026.

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