Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Returns depend on the application you deploy and the amount of benefits you are getting, which depends on how many applications you are deploying, what are the sorts of applications, and what are the requirements.
I would rate them eight if 10 was the best and one was the worst.
Observability and monitoring are areas that could be enhanced.
It was as impressive as Kafka, better than Kafka based on my experience working on the Solace and Kafka white paper.
These features are important due to scalability and resiliency.
The solution's ability to decouple message producers and consumers allows us to have high cohesion and low coupling, making it an excellent solution for that purpose.
Apache Kafka on Confluent Cloud provides real-time data streaming with seamless integration, enhanced scalability, and efficient data processing, recognized for its real-time architecture, ease of use, and reliable multi-cloud operations while effectively managing large data volumes.
Apache Kafka on Confluent Cloud is designed to handle large-scale data operations across different cloud environments. It supports real-time data streaming, crucial for applications in transaction processing, change data capture, microservices, and enterprise data movement. Users benefit from features like schema registry and error handling, which ensure efficient and reliable operations. While the platform offers extensive connector support and reduced maintenance, there are areas requiring improvement, including better data analysis features, PyTRAN CDC integration, and cost-effective access to premium connectors. Migrating with Kubernetes and managing message states are areas for development as well. Despite these challenges, it remains a robust option for organizations seeking to distribute data effectively for analytics and real-time systems across industries like retail and finance.
What are the key features of Apache Kafka on Confluent Cloud?In industries like retail and finance, Apache Kafka on Confluent Cloud is implemented to manage real-time location tracking, event-driven systems, and enterprise-level data distribution. It aids in operations that require robust data streaming, such as CDC, log processing, and analytics data distribution, providing a significant edge in data management and operational efficiency.
PubSub+ Platform supports real-time shipment tracking, IT event management in multiclouds, and connects legacy and cloud-native systems for application modernization. It's utilized for trading, streaming market data, and app-to-app messaging, enhancing event-driven architectures with reliable message queuing.
Organizations adopt PubSub+ to efficiently transport events across hybrid and cloud environments, managing audit trails and long processing tasks. The platform aids integration through dynamic data publication, event mesh capabilities, and WAN optimization. Features like seamless integration, protocol agnosticism, and flexible topic hierarchy enhance versatility. Solace Admin Utility simplifies configuration and management, while the event portal allows hybrid deployment.
What are the key features of PubSub+ Platform?PubSub+ is implemented in industries requiring real-time data handling and integration between disparate systems. Financial institutions use it for trading and streaming market data, while logistics companies benefit from real-time shipment tracking. Enterprises apply it to modernize operations by connecting legacy systems with cloud-native applications, enhancing their architecture and ensuring data reliability across environments.
We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
