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

"Google Cloud Datalab is very customizable."

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

"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."

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

"The APIs are valuable."

"We can bring data from multiple sources and easily blend it in Qlik and create a data model (star schema)."

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

"We integrate Qlik as an EU-wide BI tool, and acceptance was never an issue due to the ease of use and user interface."

"Qlik offers you all the features needed to extract the raw data from the source systems including an ETL layer to transform the data and to connect the multiple data sources into one data model, easy data sharing, security and scaling features, dashboards, and report functionality to share your data with your end-users."

"The most valuable feature of QlikSense is that you can capture the data without modifying it and then perform the ETL (extract, transform, and load) process."

"It connects very simply to data sources."

"The time it takes to deliver a dashboard is real quick."

"The extensibility of the Platform with either internally created extensions or the use of third-party provided items really opens the platform up."

More Qlik Sense pros

Cons

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

"The interface should be more user-friendly."

"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."

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

"The augmented intelligence features don't work well for the analytical user."

"This solution would be improved by adding some Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) components that are easier to interpret and design."

"The only thing I would say that comes up is that sometimes it can be a bit buggy."

"The product could be improved by implementing a user-feedback ranking system."

"A valuable improvement for this solution would be the enabling of us to host dashboards for our customers."

"Unless you pay a premium for Priority support the experience is not great."

"It would be nice to have a better system for help tickets than a community forum."

"I am starting to work with Qlik Sense SaaS these days. This environment has its own reporting service, however, one of the things that could be better for the people that are already using Nprinting, is to have a Nprinting in SaaS."

More Qlik Sense cons

Pricing and Cost Advice

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

"The product is cheap."

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

"The cost is not bad considering the flexibility and support you receive from Qlik. I believe it is worth the cost."

"Licensing can start to get expensive, but compared to other tools in this space it is about average."

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

"Licensing could be cheaper."

"Licensing is quite good, easy, but slightly expensive."

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

"Costs are a little high on the license/token side. However, if you look at the TCO, it is not too bad, particularly against Power BI."

"For on-premise enterprise users, a number of additional features come at a premium cost."

More Qlik Sense pricing and cost advice

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Top Industries

By visitors reading reviews

Construction Company

19%

Financial Services Firm

14%

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 8% of the time

Tableau Enterprise vs Google Cloud Datalab

Compared 8% of the time

Dataiku vs Google Cloud Datalab

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

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