Real-time data analysis frameworks (or stream system)

Kafka: Kafka is a messaging system that was originally developed at LinkedIn to serve as the foundation for LinkedIn’s activity stream processing pipeline. Nice talk

S4: S4 is a general-purpose, distributed, scalable, partially fault-tolerant, pluggable platform that allows programmers to easily develop applications for processing continuous unbounded streams of data.

Hedwig: Hedwig is a publish-subscribe system designed to carry large amounts of data across the internet in a guaranteed-delivery fashion from those who produce it (publishers) to those who are interested in it (subscribers).

Storm: Storm is a distributed, reliable, and fault-tolerant stream processing system. Its use cases are so broad that we consider it to be a fundamental new primitive for data processing. Introduction slide

Flume: Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. Its main goal is to deliver data from applications to Apache Hadoop’s HDFS.

Scribe: Scribe is a server for aggregating streaming log data. It is designed to scale to a very large number of nodes and be robust to network and node failures.


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