We performed a comparison between IBM Cloud Pak for Data and Qlik Compose based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable features are data virtualization and reporting."
"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's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"Scalability-wise, I rate the solution a nine or ten 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."
"Its data preparation capabilities are highly valuable."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"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."
"It is a scalable solution."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"It's a stable solution."
"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."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"I have found it to be a very good, stable, and strong product."
"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."
"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 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 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."
"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."
"The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one."
"The product must improve its performance."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"The product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve."
"The solution has room for improvement in the ETL. They have an ETL, but when it comes to the monitoring portion, Qlik Compose doesn't provide a feature for monitoring."
"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."
"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."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"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."
"Qlik's ETL and data transformation could be better."
"I'd like to have access to more developer training materials."
"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."
IBM Cloud Pak for Data is ranked 17th in Data Integration with 11 reviews while Qlik Compose is ranked 20th in Data Integration with 12 reviews. IBM Cloud Pak for Data is rated 8.0, while Qlik Compose is rated 7.6. The top reviewer of IBM Cloud Pak for Data writes "A scalable data analytics and digital transformation tool that provides useful features and integrations". On the other hand, the top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". IBM Cloud Pak for Data is most compared with IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, SSIS, Azure Data Factory and Oracle Data Integrator (ODI). See our IBM Cloud Pak for Data vs. Qlik Compose report.
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