Best Event Stream Processing Software for Apache Tomcat

Compare the Top Event Stream Processing Software that integrates with Apache Tomcat as of July 2025

This a list of Event Stream Processing software that integrates with Apache Tomcat. Use the filters on the left to add additional filters for products that have integrations with Apache Tomcat. View the products that work with Apache Tomcat in the table below.

What is Event Stream Processing Software for Apache Tomcat?

Event stream processing software enables organizations to analyze and process data in real-time as it is generated, providing immediate insights and enabling quick decision-making. This software is designed to handle large volumes of streaming data, such as sensor data, transaction logs, social media feeds, or financial market data. Event stream processing software often includes features like real-time analytics, pattern detection, event filtering, and aggregation to identify trends or anomalies. It is widely used in applications such as fraud detection, predictive maintenance, supply chain management, and real-time analytics. Compare and read user reviews of the best Event Stream Processing software for Apache Tomcat currently available using the table below. This list is updated regularly.

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    Spring Cloud Data Flow
    Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.
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