

Oracle Data Integrator and Qlik Talend Cloud compete in the data integration tools market. Based on the data comparisons, Qlik Talend Cloud might have an edge due to its comprehensive data quality tools and rich set of connectors.
Features: Oracle Data Integrator uses an EL-T approach to optimize data integration by using the processing power of databases. It includes Knowledge Modules that allow customized integration with sources like RDBMS and Hadoop. The tool also includes capabilities for dimensional modeling and error detection. Qlik Talend Cloud provides a rich set of connectors, drag-and-drop functionality, and a Java-based framework for customization, catering to diverse data management tasks.
Room for Improvement: Oracle Data Integrator users report a need for improved error handling and better platform compatibility, alongside demands for real-time integration enhancements. Initial complexity can also be an issue. Qlik Talend Cloud users call for reduced licensing costs, better support for complex transformations, and enhancements in job scheduling and debugging, along with improved real-time processing integration.
Ease of Deployment and Customer Service: Oracle Data Integrator is primarily deployed on-premises with some use of hybrid clouds, necessitating technical expertise. Customer service experiences are mixed. Qlik Talend Cloud offers deployment in both public and private clouds and while support is generally good, it could be improved with better documentation and cloud integration capabilities.
Pricing and ROI: Oracle Data Integrator's pricing is seen as high but justified for its extensive features, offering a good ROI when used efficiently. However, its licensing is complex. Qlik Talend Cloud is praised for a flexible subscription-based pricing model that is accessible, though recent price increases have raised concerns. Its bundled offerings for data management add to its value proposition.
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 can get solutions quickly, and any tickets I submit to Oracle are responded to and resolved rapidly.
The technical support of Oracle is very good; they support the Oracle Data Integrator (ODI) solution effectively.
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.
The scalability and the ability to handle multiple workloads of several parallel ETL jobs could use improvement.
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.
In terms of performance stability, I have not experienced any downtimes, crashes, or performance issues with the Oracle Data Integrator (ODI).
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.
If I use a source system like Oracle and a target system like Teradata, ODI will still run, but it struggles a bit with different infrastructures.
It would be excellent not to have to go into different areas to perform different activities but rather have a user-defined interface where we can configure a job, run it, monitor it, link packages, and link subprocesses all in one frame.
Adding AI capabilities would make Oracle Data Integrator (ODI) even better.
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.
ODI is cheaper compared to Informatica PowerCenter and IBM DataStage.
The pricing aspect of Oracle Data Integrator (ODI) is reasonable; it brings significant value to the table.
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.
The main benefits that Oracle Data Integrator (ODI) brings to the table include data quality, data completeness functionality, metadata management, and the reverse engineering feature, which allows integrating the metadata of diversified data sources with a single click.
Oracle Data Integrator (ODI) is powerful and strong if my system uses Oracle components for environments like OLTP, enterprise data warehouse, or data marts.
Oracle Data Integrator (ODI)'s ELT architecture has helped optimize my data movement and transformation significantly.
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% |
| Oracle Data Integrator (ODI) | 2.5% |
| Other | 95.1% |

| Company Size | Count |
|---|---|
| Small Business | 26 |
| Midsize Enterprise | 12 |
| Large Enterprise | 44 |
| Company Size | Count |
|---|---|
| Small Business | 21 |
| Midsize Enterprise | 12 |
| Large Enterprise | 20 |
Oracle Data Integrator offers flexible EL-T architecture, optimizing processing with database capabilities. It supports diverse data sources, automates deployment, and provides efficient data transformations, making it suitable for data warehousing and complex data environments.
Oracle Data Integrator leverages EL-T architecture to enhance processing by utilizing database strengths. It integrates with a wide array of technologies, including RDBMS, cloud, and big data. The software's Knowledge Modules enable customizable integration strategies, accelerating development. With a user-friendly interface and automation features, it simplifies metadata management and supports real-time data warehousing. Key areas such as UI performance, integration, and real-time data capabilities require enhancements. Challenges include error handling, initial setup, and compatibility with platforms like Git, Azure, and IoT services. Improvements in metadata management, scalability, and user-friendliness are needed.
What are the most important features of Oracle Data Integrator?Organizations utilize Oracle Data Integrator primarily in data warehousing, handling data from ERP systems, EBS, Fusion, and cloud databases. It aids in creating data lakes, OLTP migrations, digital health initiatives, and automation tasks, ensuring seamless integration with databases like MySQL and SQL Server.
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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