

Qlik Talend Cloud and IBM Cloud Pak for Data compete in the data integration and analytics market. IBM Cloud Pak for Data seems to have the upper hand due to its advanced AI capabilities and comprehensive feature set.
Features: Qlik Talend Cloud offers powerful tools for operational and analytical data integration, including real-time data access, transformation, and integration. It provides a large library of connectors and flexibility in adding custom features. IBM Cloud Pak for Data features Watson Studio for machine learning, Watson Knowledge Catalog for data governance, and strong integration capabilities that set it apart.
Room for Improvement: Qlik Talend Cloud faces critique regarding memory usage, system stability during installation, and limited multitasking support. Improvements are needed in error management and documentation accuracy. IBM Cloud Pak for Data is challenged by high infrastructure requirements and complexity in cloud migration, with a need for more streamlined installation and better performance monitoring.
Ease of Deployment and Customer Service: Qlik Talend Cloud offers various deployment options, including on-premises, public, and hybrid cloud environments. Its customer service is generally positive but could improve its support programs. IBM Cloud Pak for Data benefits from excellent technical support and customer service, though deployment complexity can be a challenge for some customers.
Pricing and ROI: Qlik Talend Cloud presents a cost-effective model, particularly for smaller companies, with open-source options and a perception of good ROI. IBM Cloud Pak for Data's pricing is high, making it more suitable for larger organizations, with significant ROI through its comprehensive features. Concerns remain about initial cost and complexity.
We have been able to drive responsible, transparent, and explainable AI workflow to operationalize AI and mitigate risk and regulatory compliance easily.
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.
Cloud Pak is a complicated system, and it's often difficult to find the right resource in IBM to help with specific issues.
I would rate IBM's support at about a seven or eight out of ten because we have good support coverage owing to our long association with IBM.
Customer support should be more responsive and reach and respond on time.
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.
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.
The scalability of Talend Data Integration is good; if it weren't scalable, it wouldn't be reliable.
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.
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.
I do not know if Cognos has all the features that users are looking for since we provide it as our standard and do not maintain infrastructure for other tools.
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.
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 | Market Share (%) |
|---|---|
| Qlik Talend Cloud | 1.9% |
| IBM Cloud Pak for Data | 1.3% |
| Other | 96.8% |

| Company Size | Count |
|---|---|
| Small Business | 7 |
| Large Enterprise | 12 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 11 |
| Large Enterprise | 20 |
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.
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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