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 both compete in data integration and streaming categories. Qlik Talend Cloud appears to hold the upper hand with its real-time data integration and versatile deployment capabilities, whereas Apache Kafka is preferred for scalability and high-throughput message processing.
Features: Qlik Talend Cloud excels with high-performing tools for real-time data access and transformation, a central repository for enterprise metadata sharing, and advanced monitoring capabilities. Apache Kafka is known for high-throughput message streaming, scalability, and support for a broad range of events with features like partitioning and replication.
Room for Improvement: Qlik Talend Cloud could improve with better stability during installation, reduced memory usage, and enhanced admin features and documentation. Apache Kafka faces challenges with its dependency on ZooKeeper, complexity of consumer implementations, and limited built-in monitoring tools.
Ease of Deployment and Customer Service: Qlik Talend Cloud offers versatile deployment across on-premises, cloud, and hybrid environments with commendable customer service, though users report setup complexities. Apache Kafka, appreciated for being open-source, presents deployment challenges due to configuration intricacies, but benefits from strong community support.
Pricing and ROI: Qlik Talend Cloud offers flexible subscription models with community editions, perceived as cost-effective compared to competitors, though licensing tier clarity is needed. Users report good ROI from improved data processes. Apache Kafka, valued for being open-source and free, incurring costs with enterprise versions and third-party add-ons, is praised for cost-effectiveness with high scalability and reduced operational costs.
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.
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.
The scalability of Talend Data Integration is good; if it weren't scalable, it wouldn't be reliable.
Apache Kafka is stable.
This feature of Apache Kafka has helped enhance our system stability when handling high volume data.
Apache Kafka is a mature product and can handle a massive amount of data in real time for data consumption.
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 performance angle is critical, and while it works in milliseconds, the goal is to move towards microseconds.
We are always trying to find the best configs, which is a challenge.
A more user-friendly interface and better management consoles with improved documentation could be beneficial.
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 open-source version of Apache Kafka results in minimal costs, mainly linked to accessing documentation and limited support.
Its pricing is reasonable.
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.
It allows the use of data in motion, allowing data to propagate from one source to another while it is in motion.
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 (%) |
|---|---|
| Apache Kafka | 3.8% |
| Qlik Talend Cloud | 1.8% |
| Other | 94.4% |
| Company Size | Count |
|---|---|
| Small Business | 32 |
| Midsize Enterprise | 18 |
| Large Enterprise | 49 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 11 |
| Large Enterprise | 20 |
Apache Kafka is an open-source distributed streaming platform that serves as a central hub for handling real-time data streams. It allows efficient publishing, subscribing, and processing of data from various sources like applications, servers, and sensors.
Kafka's core benefits include high scalability for big data pipelines, fault tolerance ensuring continuous operation despite node failures, low latency for real-time applications, and decoupling of data producers from consumers.
Key features include topics for organizing data streams, producers for publishing data, consumers for subscribing to data, brokers for managing clusters, and connectors for easy integration with various data sources.
Large organizations use Kafka for real-time analytics, log aggregation, fraud detection, IoT data processing, and facilitating communication between microservices.
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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