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Csound
SuperCollider
Sonic Pi
Pure Data
ChucK
Overtone
Klangmeister
Pyo
Spark Streaming
Confluent
Amazon Kinesis
Google Cloud Dataflow
Apache Flink
Leo Platform
Lenses
Striim
Csound is a sound and music computing system which was originally developed by Barry Vercoe in 1985 at MIT Media Lab. Since the 90s, it has been developed by a group of core developers. A wider community of volunteers contribute examples, documentation, articles, and takes part in the Csound development with bug reports, feature requests and discussions with the core development team.
Although Csound has a strong tradition as a tool for composing electro-acoustic pieces, it is used by composers and musicians for any kind of music that can be made with the help of the computer. Csound has traditionally been used in a non-interactive score driven context, but nowadays it is mostly used in in a real-time context. Csound can run on a host of different platforms including all major operating systems as well as Android and iOS. Csound can also be called through other programming languages such as Python, Lua, C/C++, Java, etc.
One of the main principles in Csound development is to guarantee backwards compatibility. You can still render a Csound source file from 1986 on the latest Csound release, and you should be able to render a file written today with the latest Csound in 2036.
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Based on our record, Spark Streaming seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
Spark Streaming: The component for real-time data processing and analytics. - Source: dev.to / over 1 year ago
Is a big data framework and currently one of the most popular tools for big data analytics. It contains libraries for data analysis, machine learning, graph analysis and streaming live data. In general Spark is faster than Hadoop, as it does not write intermediate results to disk. It is not a data storage system. We can use Spark on top of HDFS or read data from other sources like Amazon S3. It is the designed... - Source: dev.to / over 2 years ago
SuperCollider - A real time audio synthesis engine, and an object-oriented programming language specialised for...
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Sonic Pi - Sonic Pi is a new kind of instrument for a new generation of musicians. It is simple to learn, powerful enough for live performances and free to download.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Pure Data - Pd (aka Pure Data) is a real-time graphical programming environment for audio, video, and graphical...
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.