Sep 09, 2021
We have experiences only in Pentaho Data Integrator (open source competitor of the Oracle Data Integrator).
But OLAP exporting wasn't in our scope until now.
Qlik Talend Cloud and Apache Kafka compete in the data integration and messaging categories. Qlik Talend Cloud holds an advantage with its robust data integration suite and quality tools, whereas Apache Kafka is noted for its high throughput and scalability in data streaming.
Features: Qlik Talend Cloud stands out with its real-time ETL capabilities, allowing central repository access and Java customization for an adaptable environment. It excels with a broad range of connectors and advanced monitoring tools. Apache Kafka is distinguished by its efficient distributed messaging and data streaming, supported by persistent message queues and horizontal scalability. The solution is ideal for real-time data transactions and event-driven architectures.
Room for Improvement: Qlik Talend Cloud users note issues with technical support, memory usage, and initial setup complexity. The platform also encounters challenges with integration stability and debugging. Apache Kafka could enhance its GUI availability and stability, especially for monitoring. Complexity in deployment and dependency on Zookeeper are areas requiring attention.
Ease of Deployment and Customer Service: Qlik Talend Cloud offers diverse deployment options across on-premises and various cloud environments. Its customer service experiences mixed reviews, with some praising responsiveness. Apache Kafka supports multiple deployment options but involves higher operational complexity, relying more on community support due to its open-source nature.
Pricing and ROI: Qlik Talend Cloud follows a subscription-based pricing model, often seen as high, with various licensing options. It delivers ROI through time savings and improved data management. Apache Kafka offers a cost-effective open-source solution with no licensing fees for basic use, though commercial support increases expenses. Its strong data handling capabilities provide significant ROI compared to proprietary solutions.
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 Apache community provides support for the open-source version.
There is plenty of community support available online.
With Microsoft, expectations are higher because we pay for a license and have a contract.
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.
Customers have not faced issues with user growth or data streaming needs.
Apache Kafka is highly scalable and supports horizontal scaling by allowing you to add more brokers to the cluster and increase the number of partitions for a topic.
I need to enable my solution with high availability and scalability.
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.
Apache Kafka is stable.
This feature of Apache Kafka has helped enhance our system stability when handling high volume data.
Apache Kafka is more stable and is very good technology for asynchronous programming.
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.
Operating an Apache Kafka cluster requires expertise in partitioning, application monitoring, and capacity planning.
The performance angle is critical, and while it works in milliseconds, the goal is to move towards microseconds.
Apache Kafka groups could introduce themes or profiles of configuration to help manage this complexity without needing expertise.
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.
From a price perspective, if you are asking about Apache Kafka, I would rate it a nine.
The open-source version of Apache Kafka results in minimal costs, mainly linked to accessing documentation and limited support.
Apache Kafka itself is open source and free to use.
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.
Apache Kafka is effective when dealing with large volumes of data flowing at high speeds, requiring real-time processing.
Apache Kafka is particularly valuable for managing high levels of transactions.
The best features include high throughput with low latency and support for horizontal scaling.
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 (%) |
|---|---|
| Apache Kafka | 3.8% |
| Qlik Talend Cloud | 3.2% |
| Other | 93.0% |
| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 20 |
| Large Enterprise | 51 |
| Company Size | Count |
|---|---|
| Small Business | 21 |
| Midsize Enterprise | 12 |
| Large Enterprise | 20 |
Apache Kafka provides scalable, high-throughput, real-time data processing. Appreciated for its open-source nature and integration capabilities, Kafka supports distributed messaging and high-volume handling with essential features like message retention, replication, and partitioning.
Apache Kafka is a powerful tool for managing efficient data streams and high volumes of asynchronous messages. Its ease of setup and robust integration options make it popular among industries requiring real-time data streaming and processing. Key features such as message retention and consumer groups cater to demanding applications, while fault-tolerant design ensures reliability. Despite its advantages, Kafka can improve in areas like duplicate management, documentation, and intuitive interfaces. Challenges in configuration and monitoring tools suggest areas for enhancement, alongside reducing complexity and resource dependency.
What are the key features of Apache Kafka?Industry applications for Apache Kafka include real-time data streaming for IoT, big data management, and analytics. In finance, it supports fraud detection and transaction monitoring. Healthcare uses Kafka for patient data handling and logistics leverage its data distribution capabilities to optimize operations. Its ability to manage large-scale asynchronous communication makes it vital across sectors demanding high data throughput and reliability.
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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