

Qlik Talend Cloud and IBM Cloud Pak for Data compete in data integration and management. IBM Cloud Pak for Data appears to have the upper hand with its advanced AI capabilities and robust data governance features.
Features: Qlik Talend Cloud offers extensive real-time data integration tools, strong data access and sharing, and a comprehensive set of connectors. It allows customizations with Java code and provides powerful data quality tools for integration. IBM Cloud Pak for Data is equipped with advanced AI capabilities, robust data governance features, and seamless integration across hybrid and multi-cloud environments. It excels in data virtualization and visualization, making it a strong choice for centralized analytics.
Room for Improvement: Qlik Talend Cloud faces challenges with system crashes, memory issues, and a need for better support and stability improvements. Documentation could be more user-friendly. IBM Cloud Pak for Data needs to enhance its user interface, connector offerings, and reduce deployment complexity. Improved customer support responsiveness and simpler installation processes are also needed.
Ease of Deployment and Customer Service: Qlik Talend Cloud allows for versatile deployments on-premises, public, and hybrid cloud, though users mention initial setup challenges. It generally provides responsive customer support but lacks personalized service. IBM Cloud Pak for Data supports public and hybrid clouds, with some users facing difficulty due to extensive infrastructure requirements. Its customer support is strong but sometimes encounters delays.
Pricing and ROI: Qlik Talend Cloud offers a SaaS model with no setup costs, beneficial for open-source options, though some find the pricing high post-acquisition. It delivers time savings and error reduction, contributing to positive ROI. IBM Cloud Pak for Data is considered expensive for smaller companies but offers competitive pricing compared to peers like Informatica. It reports strong cost recovery through efficient data management, resulting in positive ROI over time.
We have been able to drive responsible, transparent, and explainable AI workflow to operationalize AI and mitigate risk and regulatory compliance easily.
It is easy to collect, organize, and analyze data no matter where it is, hence being able to make data-driven decisions.
It has helped us save a lot of time by automating repetitive data processes and reducing manual interventions.
We achieved around 20% to 30% time savings in the ETL process, reduced operational errors, and improved pipeline stability.
We actually achieved the first 18 months worth of work in the first six months.
I rate the technical support from IBM a nine out of ten because the support has been very top-notch, unparalleled, and also very professional.
Cloud Pak is a complicated system, and it's often difficult to find the right resource in IBM to help with specific issues.
The customer support for IBM Cloud Pak for Data is great and responsive.
The support team is responsive when we raise issues, and they usually provide clear guidance or solutions.
I would rate the technical support from Talend Data Quality as an 8 or 9.
The customer support for Talend Data Integration is very good; whenever I raise a ticket in the customer portal, I immediately receive an email, and follow-up communication is prompt.
I have not noticed any downtime or lagging, especially when dealing with large data, so it is relatively very scalable.
IBM Cloud Pak for Data's scalability is very good; it can be used by any size of organization.
For scalability, I rate it a nine out of ten because it is a very scalable solution that has been able to handle my organization's growth efficiently.
By using features like job parallelization and modular design, we can expand our data flows without having to rebuild everything.
Its scalability is good, as Qlik Talend Cloud can handle large amounts of data and grow as needed, especially in cloud environments.
We've set up alerts, so if we have an increasing volume and so on, it's up to us to increase CPU, increase RAM, and all those details.
The overall performance of IBM Cloud Pak for Data, particularly with IBM DataStage for ETL processes, is very good.
We have not encountered many issues with remote engines, and the interfaces are properly developed.
Once the jobs are properly designed and deployed, they run reliably without major issues.
It was not as stable when we were using TAC and on-premise systems, but currently, with Qlik Talend Cloud version 8.3 or 8.1, it is stable.
Setting up the hybrid and multi-cloud environments is a long job and it takes time.
IBM Cloud Pak for Data can be improved because processing speeds are sometimes slow.
To improve IBM Cloud Pak for Data, I suggest more out-of-the-box integration.
On the flip side, that is one of its amazing strengths, as you are not locked into a very rigid way of doing something.
Better cost and resource visibility would help teams optimize their workloads.
It would be great to have more ready-to-use connectors for modern cloud and SaaS platforms.
The setup cost is very expensive.
Regarding my experience with pricing, setup cost, and licensing, for a small organization, the price might be relatively high, but for huge enterprises such as ours, the price is relatively affordable.
The list price is high, but the flexibility in pricing is adequate.
The setup cost is very expensive.
My experience with Talend Data Integration's pricing, setup cost, and licensing is that it is a bit higher compared to other tools, making it not very affordable.
The license cost has increased significantly, leading many companies to seek more profitable options in the market.
From there, I can work my way into a more granular level, applying all of that information on top of my actual data to understand what my data looks like, where it came from, and where it went wrong, managing it throughout the cycle.
The benefits of choosing IBM Cognos, in addition to saving on cost, include having institutional knowledge about maintaining this infrastructure and enough people who have developed on Cognos in the past, which creates comfort in its use.
We have been able to save approximately 80 percent of our time. We are not doing data analysis manually, so this relieves our data department of dealing with data.
By automating daily data loading processes, we reduced manual effort by around three or four hours per day, which saved roughly 60 to 80 hours per month.
We perform profiling prior to data quality and post-data quality, and based on that, we determine how much it has improved to measure the efficiency of Talend Data Quality cleaning tools.
The feature that has made the biggest difference for me in Qlik Talend Cloud is the scheduling and automation, which helps me run ETL jobs automatically without manual work.
| Product | Mindshare (%) |
|---|---|
| Qlik Talend Cloud | 2.4% |
| IBM Cloud Pak for Data | 1.1% |
| Other | 96.5% |

| Company Size | Count |
|---|---|
| Small Business | 10 |
| Large Enterprise | 20 |
| Company Size | Count |
|---|---|
| Small Business | 21 |
| Midsize Enterprise | 12 |
| Large Enterprise | 20 |
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?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.
Qlik Talend Cloud provides robust data integration tools tailored for efficient management of large volumes, offering real-time data access, Java integration, and custom code capabilities for developers.
Qlik Talend Cloud is known for its extensive connectivity options, enabling seamless integration across different platforms, such as S3, Redshift, Oracle, and SQL Server. The central repository facilitates consistent metadata access throughout organizations, enhancing collaboration. Despite its strengths in advanced monitoring, automation, and user-friendly drag-and-drop interfaces, users face challenges with installation stability, technical support, documentation inconsistencies, and complexities in learning. Performance concerns also include multitasking limitations and excessive memory usage. The platform's licensing costs can be prohibitive for smaller companies, while demands for improved data governance and intuitive code management continue. Its applications in healthcare data parsing, ETL task automation, and diverse data platform integration demonstrate its utility, although there's a constant demand for better scalability and efficient transformations.
What are the key features?In specialized industries like healthcare, users leverage Qlik Talend Cloud for data integration and transformation, aiding in compliance and analytics. Compatibility with cloud and on-premises systems ensures adaptability to complex data tasks, facilitating business application development. Organizations focus on enhanced data ingestion and quality checks for comprehensive solutions.
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