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I struggle finding a word describing a solution that is not streaming but processes everything in phases or stages resulting in keeping everything in memory. Processing something in bulk is not the right solution.
To give you an example we currently have a mechanism that has a list of identifiers. The list has like a million entries and can be loaded into memory, processed and the memory is freed or in a streaming solution the list is loaded line by line, each line is instantly processed and the memory footprint is therefore superior to the first solution.
So what is the word to describe the first algorithm / solution.
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Batch processing is when the processing and analysis happens on a set of data that have already been stored over a period of time. An example is payroll and billing systems that have to be processed weekly or monthly. Streaming data processing happens as the data flows through a system.
Well, streaming integration is all about continuously moving any enterprise data with real high throughput in a scalable fashion, while processing that data, correlating it, and analyzing it in-memory so that you can get real value out of that data, and visibility into it in a verifiable fashion.
Stream processing is a data management technique that involves ingesting a continuous data stream to quickly analyze, filter, transform or enhance the data in real time. Once processed, the data is passed off to an application, data store or another stream processing engine.
Distributed stream processing systems involve the use of geographically distributed architectures for processing large data streams in real time to increase efficiency and reliability of the data ingestion, data processing, and the display of data for analysis.
I’m facing a similar naming issue, and decided to settle on “buffered”.
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