Horizontal scaling is possible using the ESP router or the ESP Cluster Manager to distribute events to different ESP engines on different machines. Thus vertical scaling is possible at the project level, across multiple projects, or by running multiple ESP servers. The ESP processing engine has the following distinguishing characteristics:ĮSP is multi-threaded at its "project" (~program) level and an ESP server can run multiple projects. So, while it can handle big data, it does so record by record (event by event). It constantly reads input streams and streams results as it processes. ESP is not meant to process a big data set and then return a result. stocks you should buy) in real time as the events come in. stock trades) into useful output event streams (e.g. SAS Event Stream Processing transforms raw event streams (e.g. With its massively parallel design, elastic capabilities, and optimized processing algorithms, CAS is truly a platform for big data analytics and data transformation. While CAS continues to get enhancements like pass-through SQL and SingleStore integration which enhance its dynamic I/O capabilities, CAS' data connector model offers less dynamic I/O options than SAS. CAS offers numerous APIs that allow for integration of CAS processing into SAS applications, web applications, java, etc. As such, it offers a more robust platform for integration with client applications. Unlike SAS, CAS was built from the ground-up as a back-end Viya service. CAS offers a massively parallel version of DATA Step, its own library of procedures, as well as a programming language, CASL. Viya also includes a SAS9 compute server to complement CAS where necessary. Where CAS does not offer the specific functionality that SAS does, there is generally a way to get the equivalent result with CAS. It automatically scales both vertically and horizontally to optimally utilize hardware resources when solving analytics and performing data transformation.īuilt on a paradigm of fine grained " CAS Actions" that do single, specific operations like aggregate data or run a regression, CAS offers most of the functionality of the SAS engine plus more. The CAS processing engine has the following distinguishing characteristics:ĬAS is massively parallel by design. CAS forms the back-end for all of the Viya applications including: Designed to be cloud native, CAS can add or remove resources as needed. CAS is multi-threaded by design and scales processing over multiple machines automatically. While CAS functionality already goes beyond SAS 9 in many ways ( image processing as an example), CAS is also meant to offer all the functionality of SAS 9 and more but on a modern, open, high performance, multi-machine, massively parallel processing architecture. With or without its Grid extensions, the SAS 9 engine can handle truly massive data loadsĬAS (Cloud Analytic Server) is the "next generation" SAS processing engine. While SAS is primarily designed to read/write static data like files and database tables, it also has some abilities to handle dynamic sources/targets like pipes, message queues, sockets, and more. Regardless of how it's called, its strengths are in bulk processing. While originally written as a batch engine, SAS has been extended to support every imaginable usage pattern including web services, client server, and even for transaction processing. While SAS does support two implementations of SQL, PROC SQL and PROC FEDSQL, one of SAS' strengths is its unique and flexible implementation of row processing (DATA Step) as well as its library of data transformation and analysis procedures (PROCs).īatch, Web Service, Back-End Service. To improve vertical scaling as well as offer horizontal scaling SAS/CONNECT and/or SAS Grid can spin up additional SAS 9 instances to spread the load. Many of SAS PROCs support multi-threading, however, certain analyses concerned with row order will single thread. SMP/Single Threaded Engine with Multi-Engine Scaling The SAS processing engine has the following distinguishing characteristics: All Together, these components are formally known as the SAS Compute Server and form one of the most used data processing and analytics platforms in the world as well as the back-end for many of SAS' visual interfaces including: The term, " SAS 9," is generally used to refer to Base SAS and its many extensions, SAS/CONNECT, SAS/ACCESS, SAS/STAT, IML, SAS/GRAPH, etc. Of course, "engine" is also a loaded term so here we'll take it in the broadest sense. Let's look at the different processing engines in the SAS portfolio that perform the joins, aggregations, lookups, analytics, and other data processing behind the code and visual interfaces.
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