IBM Cloud Pak for Data vs Qlik Compose comparison

IBM and Qlik are both solutions in the Data Integration category. IBM is ranked #15 with an average rating of 8.6, while Qlik is ranked #49. IBM holds a 1.1% mindshare in DI, compared to Qlik’s 0.8% mindshare. Additionally, 92% of IBM users are willing to recommend the solution, compared to 81% of Qlik users who would recommend it.

IBM Cloud Pak for Data

Read 22 IBM Cloud Pak for Data reviews

3,277 Views
3,015 Comparison Views

92% willing to recommend

Qlik Compose

Read 12 Qlik Compose reviews

2,319 Views
1,948 Comparison Views

81% willing to recommend

IBM Cloud Pak for Data

Qlik Compose

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

Qlik Compose and IBM Cloud Pak for Data offer competing solutions in data management and analytics. Qlik Compose is favorable for its cost-effective pricing and integration capabilities, whereas IBM Cloud Pak for Data stands out due to its comprehensive feature set and extensive analytics tools.

Features: Qlik Compose offers seamless data integration, automation of data warehouse creation, and robust ETL functions. IBM Cloud Pak for Data provides extensive analytics functionality, AI capabilities, and the ability to manage both structured and unstructured data.

Room for Improvement: Qlik Compose can enhance its analytics capabilities, expand its AI integration, and provide more comprehensive data governance tools. IBM Cloud Pak for Data could improve its ease of deployment, simplify its user interface, and offer more cost-effective pricing options for small to medium enterprises.

Ease of Deployment and Customer Service: Qlik Compose is recognized for its straightforward deployment and strong customer support. IBM Cloud Pak for Data, while more complex to deploy, benefits from scalable architecture suitable for enterprise-wide solutions.

Pricing and ROI: Qlik Compose is noted for competitive pricing and fast ROI, focusing on data integration capabilities. IBM Cloud Pak for Data, with higher initial setup costs, offers considerable ROI potential through its expansive features, appealing to those seeking a complete platform.

To learn more, read our detailed IBM Cloud Pak for Data vs. Qlik Compose Report (Updated: June 2026).

Buyer's Guide

IBM Cloud Pak for Data vs. Qlik Compose

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

IBM Cloud Pak for Data

Ranking in Data Integration

15th

Average Rating

8.2

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Qlik Compose

Ranking in Data Integration

49th

Average Rating

7.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2026, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.1%, down from 1.8% compared to the previous year. The mindshare of Qlik Compose is 0.8%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
IBM Cloud Pak for Data	1.1%
Qlik Compose	0.8%
Other	98.1%

Data Integration

Featured Reviews

Raman Shihan

Sr. Data Engineer at a tech vendor with 10,001+ employees

Unified data workflows have transformed how I manage sensitive analytics and end-to-end AI

One of the things that IBM Cloud Pak for Data does well is the data privacy and security that it offers. Since most of my data is very sensitive, IBM privacy framework helps me secure it very conveniently. In my experience, some of the best features that I encounter in IBM Cloud Pak for Data are the AI and Watson Assistant, which is very good. The analytics dashboard featuring all the recent history is very good with IBM. Searching for data through the unified search option is super cool. Among those features, the artificial intelligence that solves everything automatically stands out as most valuable in my day-to-day work, saving a lot of time. I can also store my data in many clouds with all the desired data. The customer service system is excellent and always willing to help. I would also add that the project analytics dashboard, ability to manage data across different cloud platforms, and end-to-end AI lifecycle are very great. IBM Cloud Pak for Data has positively impacted my organization by helping me see some return on investments. I have the ability to access all my data much quicker through the unified search option. It has also improved data security and governance in my organization very well. I've seen a 30% increase in productivity through the introduction of AI with IBM Cloud Pak for Data, which has really simplified a lot of operations that were manually tackled.

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Susheel A

Director - Metrics & Analytics at a computer software company with 1,001-5,000 employees

Efficient data warehouse automation with robust features, but may require enhancements in user-friendly self-service options and pricing flexibility for broader corporate appeal

It could enhance its capabilities in the realm of self-service options as currently, it is more suited for individuals with technical proficiency who can create pages using it. When it comes to end users who may lack technical expertise, they are limited to toggling between existing developments. To empower end users to make critical changes without relying heavily on technical expertise, it would be beneficial to introduce more user-friendly features for development and modification. If it could incorporate correlation analysis capabilities into its platform, especially in a user-friendly manner, it would greatly enhance the tool's overall utility and make it an even more outstanding solution. There is a room for improvement regarding stability.

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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

"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."

"I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography."

"IBM Cloud Pak for Data is a powerful cloud-native all-in-one easy-to-use solution that enables us to put data to work quickly and effectively."

"Its data preparation capabilities are highly valuable."

"Scalability-wise, I rate the solution a nine or ten out of ten."

"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."

"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."

"For us, IBM Cloud Pak for Data is the best option on the market at the moment."

More IBM Cloud Pak for Data pros

"I have found it to be a very good, stable, and strong product."

"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem. It's good."

"It's a stable solution."

"One of the most valuable features of this tool is its automation capabilities, allowing us to design the warehouse in an automated manner. Additionally, we can generate Data Lifecycle Policies (DLP) reports and efficiently implement updates and best practices based on proven design patterns."

"It is a scalable solution."

"There were many valuable features, such as extracting any data to put in the cloud. For example, Qlik was able to gather data from SAP and extract SAP data from the platforms."

"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."

"I like modeling and code generation. It has become a pretty handy tool because of its short ideation to delivery time. From the time you decide you are modeling a data warehouse, and once you finish the modeling, it generates all the code, generates all the tables. All you have to do is tick a few things, and you can produce a fully functional warehouse. I also like that they have added all the features I have asked for over four years."

More Qlik Compose pros

Cons

"IBM Cloud Pak for Data uses a lot of resources and it is not very resource-economic."

"More out-of-box integration."

"The solution could have more connectors."

"The solution's user experience is an area that has room for improvement."

"The product must improve its performance."

"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."

"The two main challenges that I face are setup complexity and customer support responsiveness."

"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."

More IBM Cloud Pak for Data cons

"When processing data from certain tables with a large volume of data, we encounter significant delays. For instance, when dealing with around one million records, it typically takes three to four hours. To address this, I aim to implement performance improvements across all tables, ensuring swift processing similar to those that are currently complete within seconds. The performance issue primarily arises when we analyze the inserts and updates from the source, subsequently dropping the table. While new insertions are handled promptly, updates are processed slowly, leading to performance issues. Despite consulting our Qlik vendors, they were unable to pinpoint the exact cause of this occurrence. Consequently, I am seeking ways to optimize performance within Qlik Compose, specifically concerning updates."

"I believe that visual data flow management and the transformation function should be improved."

"I'd like to have access to more developer training materials."

"I don't think Qlik can be used in a high-volume scenario. It didn't work for us."

"It would be better if the first level of technical support were a bit more technically knowledgeable to solve the problem. I think they could also improve the injection of custom scripts. It is pretty difficult to add additional scripts. If the modeling doesn't give you what you want, and you want to change the script generated by the modeling, it is a bit more challenging than in most other products. It is very good with standard form type systems, but if you get a more complicated data paradigm, it tends to struggle with transforming that into a model."

"My issues with the solution's stability are owing to the fact that it has certain bugs causing issues in some functionalities that should be working."

"Qlik's ETL and data transformation could be better."

"For more complex work, we are not using Qlik Compose because it cannot handle very high volumes at the moment. It needs the same batching capabilities that other ETL tools have. We can't batch the data into small chunks when transforming large amounts of data. It tries to do everything in one shot and that's where it fails."

More Qlik Compose cons

Pricing and Cost Advice

"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."

"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."

"Cloud Pak's cost is a little high."

"It's quite expensive."

"The solution's pricing is competitive with that of other vendors."

"I think that this product is too expensive for smaller companies."

"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."

"The solution is expensive."

"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."

"The price of the solution is expensive."

"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Manufacturing Company

10%

Computer Software Company

University

Financial Services Firm

13%

Government

11%

Manufacturing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	10
Large Enterprise	20

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	3
Large Enterprise	6

Questions from the Community

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

My experience with pricing, setup cost, and licensing is that the cost of the product can be a bit higher, especially for a company working on a tight budget.

See all answers

What needs improvement with IBM Cloud Pak for Data?

One of the improvements I think should be made to IBM Cloud Pak for Data is that the cost of the product is a bit higher. Besides cost, I think something that is needed for improvement is that more...

See all answers

What is your primary use case for IBM Cloud Pak for Data?

My main use case for IBM Cloud Pak for Data is that it is fully scalable and a scalable platform for data. I use it to provide data solutions for my customers. I also use it to provide various indu...

See all answers

Which ETL tool would you recommend to populate data from OLTP to OLAP?

There are two products I know about * TimeXtender : Microsoft based, Transformation logic is quiet good and can easily be extended with T-SQL , Has a semantic layer that generates metat data for cu...

See all answers

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Azure Data Factory vs IBM Cloud Pak for Data

Compared 6% of the time

Denodo vs IBM Cloud Pak for Data

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Compared 10% of the time

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Compared 8% of the time

WhereScape RED vs Qlik Compose

Compared 6% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Compose

Compared 6% of the time

FME vs Qlik Compose

Compared 3% of the time

More Qlik Compose Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

June 2026

Download IBM Cloud Pak for Data product report

Buyer's Guide

Qlik Compose

June 2026

Download Qlik Compose product report

Also Known As

Cloud Pak for Data

Compose, Attunity Compose

Overview

IBM Cloud Pak for Data is a comprehensive platform integrating data management, AI, and machine learning capabilities tailored for hybrid environments. It's renowned for enhancing productivity through efficient data analytics and management.

This platform offers data virtualization, robust analytics, and AI-driven processes. Its integration capabilities, including IBM MQ and App Connect, facilitate seamless data connections. Users benefit from containerization, data governance, and compatibility with hybrid systems, improving decision-making and management productivity. However, the requirement of extensive infrastructure and performance challenges can impact scalability for small businesses.

What are the key features of IBM Cloud Pak for Data?

Watson Knowledge Catalog: Organizes data for accessibility and insight extraction.
Data Virtualization: Provides a unified data view across sources without copying data.
Robust Analytics: Offers advanced analytics tools for data-driven decision-making.
Integration Capabilities: Includes IBM MQ and App Connect for seamless data integration.
AI and Machine Learning: Supports AI-driven insights and learning models.

What benefits or ROI should users expect?

Enhanced Productivity: Streamlines data management processes, enhancing efficiency.
Better Business Decisions: Utilizes analytics for informed strategic choices.
Improved Data Governance: Ensures compliance and quality in data handling.
Collaboration: Encourages teamwork with a comprehensive platform supporting analytics.

In the financial and banking sectors, IBM Cloud Pak for Data is utilized for data management tasks like spend analytics and contract leakage analysis. It's used for data integration, machine learning, and AI-driven analytics to transform data into valuable insights in industries such as FinTech and consultancy.

IBM

Qlik Compose enhances data management with ETL capabilities, data integration with CDC, and real-time replication. Its intuitive interface enables easy data modeling and automation, supporting various database integrations.

Qlik Compose is designed for efficient data preparation, migration, and warehouse generation. It incorporates ETL functionalities and data integration with CDC, allowing users to effortlessly create data marts without code. Its automation features facilitate warehouse design while graphical representations and connectivity options increase versatility across multiple sources. Users value its stability, scalability, and the support provided, although improvements in ETL functionalities, performance for large datasets, and NoSQL integration are needed. The solution is widely used in business intelligence with tools like Qlik Replicate for real-time data replication and requires direct SQL for complex transformations.

What are the key features of Qlik Compose?

ETL Capabilities: Simplifies data extraction, transformation, and loading
Data Integration with CDC: Enables real-time data replication
Intuitive Interface: Facilitates easy data modeling and automation
Drag-and-Drop Functionality: Streamlines data task management
Auto-Mapping: Enhances integration of multiple data sources
No-Code Data Marts Creation: Reduces dependency on technical skills

What benefits should users consider in the reviews?

Stability and Scalability: Reliable functioning for growing data needs
Technical Support: Availability of assistance for troubleshooting
Real-Time Replication Capabilities: Efficient data processing and analytics
Low-Code Development: Simplifies complex data handling processes

In industries, Qlik Compose is implemented for enhancing data preparation, migration, and warehousing. It is used in small projects or straightforward data integration tasks and supports business intelligence efforts by offering low-code capabilities, enabling companies to deliver tailored analytics solutions efficiently.

Qlik

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

Poly-Wood

Buyer's Guide

IBM Cloud Pak for Data vs. Qlik Compose

June 2026

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