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Apache Samza

Apache Samza is a distributed Stream Processing Framework (SPF) (stream processing) for building stateful applications that process real-time data feeds.

  • Distributed stream processing for real-time data pipelines and applications (stream processing)
  • Stateful processing with local storage for managing application state (data management)
  • Support for event-at-a-time and windowed processing over streams (stream analytics)
  • Pluggable architecture for various execution engines and messaging systems (integration)
  • Resource management and deployment options including YARN and standalone modes (orchestration)

More About Apache Samza

Apache Samza is a framework for processing continuous data streams (stream processing) and building stateful applications that operate on real-time events. It addresses use cases where data arrives as unbounded streams, such as log data, messaging events, monitoring metrics, and user activity, and where applications need to react, enrich, or aggregate this data with low latency.

The project provides a high-level Application Programming Interface (API) for defining stream processing jobs (application framework), including operations such as filtering, mapping, joins, and aggregations over streams. Samza supports event-at-a-time processing and windowed operations, allowing developers to express time-based or count-based windows over data streams. It also supports stateful processing, where application state is stored locally and accessed efficiently during event handling.

Samza’s architecture separates the processing framework from the underlying execution engine and messaging system (integration). It was designed to work with a distributed messaging bus and a durable log, and the framework exposes a pluggable system layer that can integrate with multiple stream sources and sinks. The project documentation describes integration patterns where Samza jobs consume events from a messaging system, process them, maintain state, and emit derived events or updates to downstream systems.

For deployment and resource management (orchestration), Apache Samza supports running on cluster resource managers such as Apache YARN, as well as in standalone mode. This enables enterprises to run Samza jobs in existing Hadoop or YARN-based environments or as independent services. Samza containers run tasks that execute user-defined processing logic, with the framework handling task assignment, scaling, and fault tolerance.

State management in Samza uses local storage backed by changelog streams (data management). Application state is maintained on the same host as the processing task for performance, while changes to the state are written to a changelog for durability and recovery. On failure or task migration, the state can be restored from the changelog streams, which supports exactly-once or at-least-once processing semantics as documented by the project.

In enterprise environments, Apache Samza is used to construct real-time data pipelines, monitoring and alerting systems, and event-driven services (event-driven architecture). It fits in directories and taxonomies under categories such as stream processing frameworks, data engineering platforms, and real-time analytics infrastructure. Its design around pluggable system integration, local state management, and cluster deployment makes it suitable for organizations that operate large-scale data streams and require continuous processing rather than batch workflows.