A lightweight real-time big data streaming engine built on Akka for high-throughput, low-latency data processing.
Apache Gearpump is a lightweight real-time big data streaming engine built on the Akka framework. It processes continuous data streams with high throughput and low latency, addressing the need for efficient, scalable streaming solutions in big data environments.
Data engineers and developers building real-time streaming applications, particularly those working with big data clusters who require high-performance, Akka-based processing.
Developers choose Gearpump for its simplicity and power, offering a streamlined alternative to heavier streaming frameworks with proven performance benchmarks and integration with Akka's robust actor model.
Mirror of Apache Gearpump (Incubating)
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Benchmarks show processing 18 million messages per second with 8ms latency on a 4-node cluster, as detailed in the performance report link.
Leverages Akka's actor hierarchy for inherent fault tolerance and concurrency, providing a scalable and resilient architecture as highlighted in the README.
Includes a Docker-based integration test system for reliable and reproducible testing, mentioned in the README under 'How to run Gearpump integration test'.
Models streaming with minimalism inspired by the gear pump concept, offering a streamlined alternative to heavier frameworks like Apache Storm or Flink.
As an Apache incubator project, it may have fewer features, less stability, and a smaller community compared to established streaming frameworks like Apache Flink or Spark Streaming.
Requires expertise in Scala and Akka, limiting accessibility for teams using other languages such as Java or Python, and adding a learning curve for broader adoption.
Building from source involves sbt commands, network dependency, and proxy configuration issues, as noted in the 'How to Build' section, which can be error-prone for new users.