What are some common technologies used for stream processing in real-time data processing systems?
- Apache Kafka, Apache Flink, Apache Storm, Apache Samza
- Hadoop, MongoDB, Redis, PostgreSQL
- Python, Java, C++, Ruby
- TensorFlow, PyTorch, Keras, Scikit-learn
Common technologies for stream processing in real-time data processing systems include Apache Kafka, Apache Flink, Apache Storm, and Apache Samza. These technologies are specifically designed to handle high-throughput, low-latency data streams, offering features like scalability, fault tolerance, and exactly-once processing semantics. They enable real-time processing of data streams, facilitating applications such as real-time analytics, monitoring, and event-driven architectures.
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