IBM Cloud Pak for Data vs Qlik Replicate comparison

IBM and Qlik are both solutions in the Data Integration category. IBM is ranked #24 with an average rating of 7.7, while Qlik is ranked #16 with an average rating of 8.0. IBM holds a 2.0% mindshare in DI, compared to Qlik’s 3.0% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 100% of Qlik users who would recommend it.

IBM Cloud Pak for Data

Read 13 IBM Cloud Pak for Data reviews

2,349 Views
2,208 Comparison Views

86% willing to recommend

Qlik Replicate

Read 18 Qlik Replicate reviews

4,507 Views
3,200 Comparison Views

100% willing to recommend

IBM Cloud Pak for Data

Qlik Replicate

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Executive SummaryUpdated on Dec 19, 2024

Qlik Replicate and IBM Cloud Pak for Data both compete in the data integration and management space. Qlik Replicate seems to have the upper hand due to its strong real-time data capture and replication capabilities.

Features: Qlik Replicate is noted for its real-time change data capture, seamless data replication without impacting source databases, and strong data manipulation capabilities. It also offers easy data integration across various endpoints with robust logging functionalities. IBM Cloud Pak for Data stands out with advanced data preparation, AI integration through Watson Studio, and strong data governance via Knowledge Catalog. Its data virtualization feature enables efficient data analysis and connection to multiple data sources.

Room for Improvement: Qlik Replicate could enhance error message clarity, user interface, and connectivity with multiple data destinations. It also requires improvements in support services and API handling. IBM Cloud Pak for Data needs a more streamlined setup and deployment process, expanded connector availability, and better handling of heavy infrastructure demands. Enhancements in performance and support for diverse connectors are also necessary.

Ease of Deployment and Customer Service: Qlik Replicate functions well across public and on-premises environments and is generally praised for proactive support, though response times can improve. IBM Cloud Pak for Data primarily supports public and hybrid clouds but faces challenges with its user interface and infrastructure needs. Its customer service requires quick and decisive improvement.

Pricing and ROI: Qlik Replicate is viewed as costly for small businesses, with a core-based licensing model favoring large data sets but discouraging smaller deployments. Despite high costs, it offers ROI through reduced database usage and maintenance. IBM Cloud Pak for Data targets larger enterprises with high costs linked to advanced functionalities like AI, and is regarded as complex in pricing, yet it promises ROI via time-saving and operational efficiency.

To learn more, read our detailed IBM Cloud Pak for Data vs. Qlik Replicate Report (Updated: July 2025).

Buyer's Guide

IBM Cloud Pak for Data vs. Qlik Replicate

July 2025

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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

24th

Average Rating

7.8

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Qlik Replicate

Ranking in Data Integration

16th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 2.0%, up from 1.7% compared to the previous year. The mindshare of Qlik Replicate is 3.0%, up from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Michelle Leslie

Data asset management engineer at a tech services company with 1-10 employees

Starts strong with data management capabilities but needs a demo database

What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.

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KrishnaBaddam

Presales Manager at Artha Solutions

Lightweight tool, ensures that data is replicated across different systems and simplify complex tasks such as defining relationships

Qlik Compose is something that will automate user's overall data modernization. Here data modernization includes data modeling, ETL jobs, etc. But the advantage is users can automate the overall process of data engineering and data modeling through Qlik Compose. I think that's useful when users are able to manage 60% of the workload automated. That will be very useful. That's fantastic. Replicate does not have a great AI capability. AI capabilities are present in Qlik Sense. Qlik Replicate is a very light tool. It is only meant to capture data from the log files, get the data, and transfer it, read that table structure, create the table structure, and transfer the data whenever there is a change. So, it basically integrates with the kernel of the operating system. The way it works is that these replicate tools will integrate with the kernel of the operating system, and they will access the redo log files of the database. The redo log should have access to all the files of the structure of the schema, too. So, using that technique, they redo all the data structures, create a similar structure, and replicate the structure in the target schema, table, and database. After that is done, it will start tracing the instances that are happening. For example, if data is inserted into the table, then an insert is fired on the statement on the table. So, that particular insert is captured. And based on that insert statement, it will pull the SQL query and say, "Okay, there is an insert. I need to get that data." It will get the data from the redo log itself rather than going to a database. Then, it will just pass that transaction into the target system, where it will just insert the data. And this happens instantaneously, within a microsecond. So, if there is an insert, an update, or a delete, everything is transferred immediately. It is picked from the redo log because it comes to the redo log, and then the redo log sends it to Qlik Replicate and Replicate to the target system on which Replicate is installed.

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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

"Its data preparation capabilities are highly valuable."

"DataStage allows me to connect to different data sources."

"The most valuable features are data virtualization and reporting."

"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."

"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."

"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."

"Cloud Pak is a very, very, very good system."

"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."

More IBM Cloud Pak for Data pros

"Support has been great."

"The CDC and the flexibility to use QVD as a source are the most valuable features of Qlik Replicate."

"Low-priced reporting and analytics solution, with good scalability and stability. It has on-premises and cloud versions that are cohesive and can integrate well."

"A valuable feature of Qlik Replicate is that you do not need ETL. It's easy to use—you choose two systems and it automatically replicates them. Even if there is no CDC available, if you insert it and update it, and there is nothing to find out, then you can use Qlik Replicate. It's a good product."

"We use Qlik Replicate to change data capture of databases in production environments."

"The cost is under control with this solution, unlike other services where it's not."

"The most useful functions of Qlik Replicate are the data manipulation to transformations."

"A pretty good series of connectors is one of the best features of Qlik Replicate."

More Qlik Replicate pros

Cons

"The solution's catalog searching or map search needs to be improved."

"The technical support could be a little better."

"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."

"What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated."

"The solution could have more connectors."

"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."

"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."

"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

More IBM Cloud Pak for Data cons

"Some features on the graphical user interface are clunky."

"Support response times could be improved as there are sometimes delays in receiving replies to support cases."

"Some features can also be overly dependent on each other. So, there is room for improvement."

"We would like to see more details in messages about errors with the system."

"It would be better if the solution’s pricing were more obvious."

"The product should improve its licensing limitation."

"We'd like better connectivity."

"The disadvantage is people are not going for this license because it is not marketed properly."

More Qlik Replicate cons

Pricing and Cost Advice

"It's quite expensive."

"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."

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

"The solution is expensive."

"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."

"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."

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

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

"Qlik Replicate is not expensive, compared to GoldenGate."

"Overall, Qlik is an expensive solution. You need to pay for all additional features that you would like to use."

"Unlike Azure, where you pay based on consumption, Qlik Replicate seems to charge per endpoint."

"Pricing for this solution is very reasonable."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Qlik Replicate's pricing a nine out of ten."

"Qlik Replicate is mainly suited for large companies. However, it is too costly for small businesses. Its pricing is high."

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Top Industries

By visitors reading reviews

Financial Services Firm

30%

Manufacturing Company

10%

Computer Software Company

Government

Financial Services Firm

18%

Insurance Company

11%

Computer Software Company

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about IBM Cloud Pak for Data?

DataStage allows me to connect to different data sources.

See all answers

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

The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.

See all answers

What needs improvement with IBM Cloud Pak for Data?

See all answers

What do you like most about Qlik Replicate?

The main valuable feature is its real-time change data capture (CDC) capabilities, which process data with minimal latency. There is not much delay. It also performs well with batch-wise data appli...

See all answers

What needs improvement with Qlik Replicate?

Qlik Replicate could be improved in the next release by incorporating more monitoring options to monitor the logs. Currently, log monitoring is not easily accessible, so there should be improvement...

See all answers

What is your primary use case for Qlik Replicate?

My customer's main use case for Qlik Replicate is with one of the payment banks in India. We have implemented this Replicate project for their source data migration to cloud solutions. They wanted ...

See all answers

Comparisons

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 41% of the time

Denodo vs IBM Cloud Pak for Data

Compared 12% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs IBM Cloud Pak for Data

Compared 11% of the time

Azure Data Factory vs IBM Cloud Pak for Data

Compared 10% of the time

Palantir Foundry vs IBM Cloud Pak for Data

Compared 8% of the time

More IBM Cloud Pak for Data Competitors

Oracle GoldenGate vs Qlik Replicate

Compared 17% of the time

AWS Database Migration Service vs Qlik Replicate

Compared 16% of the time

Qlik Compose vs Qlik Replicate

Compared 8% of the time

Fivetran vs Qlik Replicate

Compared 7% of the time

Azure Data Factory vs Qlik Replicate

Compared 7% of the time

More Qlik Replicate Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

July 2025

Download IBM Cloud Pak for Data product report

Buyer's Guide

Qlik Replicate

July 2025

Download Qlik Replicate product report

Also Known As

Cloud Pak for Data

Replicate, Qlik Replicate

Overview

IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.

Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.

IBM

Qlik Replicate is a data replication solution for replicating data from one source database to another for business intelligence software. It offers data manipulation and transformations, replication without impacting source databases, and ease of use without needing ETL. The solution is stable and user-friendly, with detailed logging and support.

Qlik Replicate has improved the organization by allowing each team to replicate their data into a single-source data location. The most important feature of Qlik Replicate is its ability to replicate and update records without needing a programmer.

Qlik

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

American Cancer Society, Fanzz, SM Retail, Smart Modular, Tangerine Bank, Wellcare

Buyer's Guide

IBM Cloud Pak for Data vs. Qlik Replicate

July 2025

Free Report: IBM Cloud Pak for Data vs. Qlik Replicate

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