Csound
SuperCollider
Sonic Pi
Pure Data
ChucK
Overtone
Klangmeister
Pyo
Google Cloud Dataflow
Google BigQuery
Amazon EMR
Databricks
Google Cloud Dataproc
Qubole
Snowflake
Confluent
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.
CsoundNo Csound videos yet. You could help us improve this page by suggesting one.
Based on our record, Google Cloud Dataflow seems to be more popular. It has been mentiond 14 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.
Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago
This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago
You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago
It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / almost 2 years ago
SuperCollider - A real time audio synthesis engine, and an object-oriented programming language specialised for...
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
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 EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Pure Data - Pd (aka Pure Data) is a real-time graphical programming environment for audio, video, and graphical...
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
