Qlik Talend Cloud and Prometheus-AI Platform both excel in data integration and monitoring. Qlik Talend Cloud is favored for its comprehensive data integration capabilities, while Prometheus is recognized for its flexible monitoring and cost-effectiveness.
Features: Qlik Talend Cloud offers a robust set of tools for data integration, including a wide array of components essential for custom jobs, vast data volume management, and an extensive range of connectors for data transformation. Prometheus-AI Platform stands out for its reliable metric collection, integration capabilities, and lightweight configuration, making it a widely adopted tool in technology companies for monitoring large-scale environments.
Room for Improvement: Qlik Talend Cloud faces memory consumption and system stability challenges, with users reporting crashes and a lack of multitasking support. Enhancing error handling and JavaScript debugging support is necessary. Prometheus-AI Platform could improve its user interface and documentation. Users suggest expanding visualization capabilities and enhancing integration and security features.
Ease of Deployment and Customer Service: Qlik Talend Cloud offers multiple deployment options, including cloud and on-premises, with generally responsive customer service. However, documentation clarity could be improved. Prometheus-AI Platform provides diverse deployment choices and strong community support but requires effort for initial setup and configuration.
Pricing and ROI: Qlik Talend Cloud's subscription-based pricing is flexible but higher compared to competitors. Its comprehensive package results in significant ROI through time and process efficiencies. Prometheus-AI Platform, being open-source, offers a cost-effective solution, ensuring minimal expense for robust monitoring, providing excellent ROI for businesses.
Using open-source Prometheus saves me money compared to AWS native services.
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.
Prometheus does not offer traditional technical support.
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.
Prometheus is scalable, with a rating of ten out of ten.
By using features like job parallelization and modular design, we can expand our data flows without having to rebuild everything.
The scalability of Talend Data Integration is good; if it weren't scalable, it wouldn't be reliable.
Its scalability is good, as Qlik Talend Cloud can handle large amounts of data and grow as needed, especially in cloud environments.
Deploying it on multiple instances or using Kubernetes for automatic management has enhanced its stability.
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.
On the flip side, that is one of its amazing strengths, as you are not locked into a very rigid way of doing something.
It would be great to have more ready-to-use connectors for modern cloud and SaaS platforms.
Talend Data Integration can be improved by reducing the license cost, as it is a bit high compared to other tools, which can be a burden for small-scale companies wanting to buy a license.
Prometheus is cost-effective for me as it is free.
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.
It allows me to save money by avoiding costs associated with AWS native services like CloudWatch or Amazon Prometheus.
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 | 6.2% |
| Prometheus-AI Platform | 2.0% |
| Other | 91.8% |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 8 |
| Large Enterprise | 13 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 11 |
| Large Enterprise | 18 |
Prometheus-AI Platform offers flexible solutions for collecting, visualizing, and comparing metrics, appreciated for its scalability, rich integrations, and open-source adaptability.
Prometheus-AI Platform provides a reliable framework for monitoring and analyzing metrics across diverse environments. With extensive API support, it supports data collection, querying, and visualization, integrating seamlessly with tools like Grafana. High availability, scalability, and lightweight configuration make it suitable for traditional and microservice environments, while community support enhances its utility. Though its query language and interface require improvements for better ease of use, and with calls for stronger integration options, the platform remains a leading choice for comprehensive metric analysis.
What are Prometheus-AI Platform's main features?Companies leverage Prometheus-AI Platform across various industries, utilizing it to monitor and analyze metrics from applications and infrastructure. It is extensively used in financial services and IT sectors for collecting, scraping logs, and monitoring Kubernetes deployments. Deployed both on-premise and in cloud environments like Azure and Amazon, it supports system and application metrics analysis, ensuring a comprehensive view for developers.
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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