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  2. Apache Kafka - Wikipedia

    en.wikipedia.org/wiki/Apache_Kafka

    Apache Kafka is a distributed event store and stream-processing platform. It is an open-source system developed by the Apache Software Foundation written in Java and Scala.The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds.

  3. Apache Samza - Wikipedia

    en.wikipedia.org/wiki/Apache_Samza

    Samza allows users to build stateful applications that process data in real-time from multiple sources including Apache Kafka.. Samza provides fault tolerance, isolation and stateful processing.

  4. Stream processing - Wikipedia

    en.wikipedia.org/wiki/Stream_processing

    By way of illustration, the following code fragments demonstrate detection of patterns within event streams. The first is an example of processing a data stream using a continuous SQL query (a query that executes forever processing arriving data based on timestamps and window duration). This code fragment illustrates a JOIN of two data streams ...

  5. Reactive Streams - Wikipedia

    en.wikipedia.org/wiki/Reactive_Streams

    On April 30, 2015 version 1.0.0 of Reactive Streams for the JVM was released, [5] [6] [11] including Java API, [12] a textual specification, [13] a TCK and implementation examples. It comes with a multitude of compliant implementations verified by the TCK for 1.0.0, listed in alphabetical order: [11] Akka Streams [14] [15] MongoDB [16]

  6. Stream (computing) - Wikipedia

    en.wikipedia.org/wiki/Stream_(computing)

    Stream editing processes a file or files, in-place, without having to load the file(s) into a user interface. One example of such use is to do a search and replace on all the files in a directory, from the command line. On Unix and related systems based on the C language, a stream is a source or sink of data, usually individual bytes or characters.

  7. Data stream mining - Wikipedia

    en.wikipedia.org/wiki/Data_stream_mining

    Data Stream Mining (also known as stream learning) is the process of extracting knowledge structures from continuous, rapid data records.A data stream is an ordered sequence of instances that in many applications of data stream mining can be read only once or a small number of times using limited computing and storage capabilities.

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