

Qlik Talend Cloud and Amazon Kinesis are key players in the data integration and streaming platform category. Qlik Talend Cloud appears to have an edge in comprehensive data integration features, while Amazon Kinesis leads in real-time data processing due to its simplicity and AWS integration.
Features: Qlik Talend Cloud is known for its extensive connector library, real-time integration capabilities, and advanced customization through Java code. Amazon Kinesis offers simplicity, real-time data processing, and seamless integration with other AWS services while maintaining ease of management as a fully hosted service.
Room for Improvement: Qlik Talend Cloud faces challenges with usability and high memory consumption, suggesting improvements in testing and documentation. Amazon Kinesis could enhance scalability and reduce complexity in setup, with an emphasis on better handling of large data volumes and order constraints in data streaming.
Ease of Deployment and Customer Service: Qlik Talend Cloud supports flexible deployment in hybrid environments, suitable for both cloud and on-premises setups. Amazon Kinesis primarily supports public cloud deployment. Both platforms generally receive favorable customer service feedback, though Qlik Talend Cloud users report mixed experiences with initial setup and technical assistance.
Pricing and ROI: Qlik Talend Cloud operates with a cost-effective open-source model, but commercial licensing can be pricey. Amazon Kinesis is valued for its competitive cloud-hosted pricing, with both platforms achieving strong ROI through significant time savings and process optimizations, leading to lower operational expenses.
With Lambda, there is no need for data transfer charges, which is beneficial for less frequent workloads.
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.
We receive prompt support from AWS solution architects or TAMs.
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.
Amazon Kinesis provides auto-scaling with streams that handle large volumes well.
I would rate the scalability of Amazon Kinesis as a nine.
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.
I would rate the stability of Amazon Kinesis as high, giving it a 10.
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.
There is no lack of functions in Amazon Kinesis. Functionality-wise, we feel it's complete.
Amazon Kinesis could improve its pricing to be more competitive, especially for large volumes.
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.
Amazon Kinesis and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.
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.
Lambda's scalability, seamless integration with other AWS services, and support for multiple programming languages are very beneficial.
Amazon Kinesis integrates easily with the AWS environment.
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 | 3.2% |
| Amazon Kinesis | 4.0% |
| Other | 92.8% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 10 |
| Large Enterprise | 10 |
| Company Size | Count |
|---|---|
| Small Business | 21 |
| Midsize Enterprise | 12 |
| Large Enterprise | 20 |
Amazon Kinesis provides real-time data streaming with seamless AWS integration, ideal for analytics, data transformation, and external customer feeds. It offers cost-effective data management with high throughput and low latency, supporting multiple programming languages.
Amazon Kinesis enables organizations to manage real-time data streams efficiently. Its integration with AWS ensures seamless setup and operation, while features like auto-scaling and fault tolerance make it reliable for diverse data sources such as IoT devices and server logs. The platform's ability to handle large-scale event-driven systems and dynamic workloads makes it suitable for complex streaming architectures. Despite some challenges with costs and setup complexity, Kinesis remains a popular choice for its efficient data management and processing capabilities.
What are the key features of Amazon Kinesis?In industries such as IoT, finance, and entertainment, Amazon Kinesis facilitates the real-time ingestion and processing of data streams. It connects seamlessly to data lakes and warehouses, enabling businesses to harness data-driven insights without performance loss. This capability is essential for managing dynamic workloads and large-scale event systems. By supporting tools like KDS, Firehose, and Video Streams, Kinesis empowers organizations to respond quickly to changing data environments, enhancing operational effectiveness across different sectors.
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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