

Qlik Talend Cloud and erwin Data Modeler compete in the data management and integration category. While Qlik Talend Cloud is advantageous for flexibility and integration capabilities, erwin Data Modeler shines in modeling and visualization, each excelling in their respective strengths.
Features: Qlik Talend Cloud offers extensive data integration features, enabling real-time data access and a robust repository for enterprise metadata. Its open-source data quality tools and wide community support are notable. Erwin Data Modeler excels in providing robust database modeling capabilities, offering reverse engineering, version control, and comprehensive management of logical and physical databases.
Room for Improvement: For Qlik Talend Cloud, user reviews point to areas like stability, better memory usage, improved documentation, and error handling as needed enhancements. Erwin Data Modeler users suggest a simplified interface, improved reporting, enhanced platform integration, and better NoSQL database handling.
Ease of Deployment and Customer Service: Qlik Talend Cloud offers flexible deployment across private, public, and hybrid clouds, despite sometimes challenging setups. Responsive support is noted, although more direct assistance is desired. Erwin Data Modeler, mainly on-premises, offers less deployment flexibility but is commended for excellent support and maintenance.
Pricing and ROI: Qlik Talend Cloud, as open-source with a subscription model, is cost-effective but considered high-priced compared to some rivals, yet showing positive ROI by reducing manual tasks. Erwin Data Modeler is seen as expensive but offers strong ROI in enterprise settings due to its modeling capabilities and licensing benefits for larger companies.
If three engineers save ten hours each per month using erwin Data Modeler versus manual modeling, that equals three hundred sixty hours saved per year.
It replaces manual charting in Visio with a structured tool, providing significant return on investment.
If the modeling is compromised, then the entire structure will be compromised.
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.
The quality and speed of their support are excellent; everyone is very helpful, and they can solve problems quickly.
This rating reflects my ability to effectively utilize the tool and get support for licensing issues, installation errors, or corrupted repositories end-to-end.
Quest is committed to keeping the product robust.
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 would rate it probably a nine, making it a leader in data modeling.
erwin Data Modeler had a very good standardization infrastructure and supported a controlled multi-user environment with check-ins and check-outs.
Performance can degrade during larger collaborations and requires tuning for optimal performance.
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.
This lack of an auto-save methodology can be improved so that if a system crash occurs, work can be saved and rework can be avoided.
New versions often introduce enhanced features but may cause model crashes due to memory exhaustion.
Sometimes when I want to open the attribute editor, it stops working and the whole application freezes.
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.
The previous version of erwin Data Modeler used to crash unaccountably, but this one hasn't ever crashed on me, so it's been a lot more stable than the previous version that we had.
There are many features, and I would expect good documentation detailing each feature, including when and how to use it, to be very useful because data modeling is not very popular in the data area and there aren't many educational videos regarding erwin Data Modeler.
Erwin Data Modeler could improve in areas such as the interface, as there are features like copy and paste, creating duplicates, and the visualization elements and toolbars which feel quite old.
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.
For a cloud or SaaS standard edition, it typically runs around two hundred to two hundred ninety-nine US dollars per month.
It is more targeted toward an enterprise level since organizations looking to store business information and relationship values may consider the pricing.
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.
One of the key aspects of data governance is defining the data dictionary and clearly identifying which data is accessible by whom and what is not accessible, particularly regarding PII-related data.
The way the data is organized and you have a visual of that organization helps a great deal in terms of trying to remember what you did and trying to retrieve the information.
One of the best aspects of the tool is its reverse engineering capability.
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 | 1.8% |
| erwin Data Modeler | 0.3% |
| Other | 97.9% |

| Company Size | Count |
|---|---|
| Small Business | 15 |
| Midsize Enterprise | 3 |
| Large Enterprise | 34 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 11 |
| Large Enterprise | 20 |
Erwin Data Modeler provides an effective approach to visualizing and managing data models. It assists in creating, reversing, and synchronizing data models with ease, supporting logical and physical transitions while enhancing understanding across teams.
Erwin Data Modeler is a comprehensive tool designed for professional database management. It offers capabilities to organize and enforce standards, automating script generation with robust reverse engineering and DDL output. Users can manage complex data environments, capitalize on integration with data intelligence, and maintain large-scale databases smoothly. Despite its strengths, improvements in multi-language support, database integration, and reporting features are needed. Users benefit from extensive support for conceptual, logical, and physical database modeling, enhancing architectural design and data governance for platforms like SQL Server, Oracle, and Teradata.
What are the key features of Erwin Data Modeler?Erwin Data Modeler finds application in industries focused on robust data management, implementing it for enterprise data warehouses, business domain models, and operational systems. It supports architectural design and governance, aligning with business applications demanding precise data representation and visualization.
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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