The use of real-time data streams in data-driven computational science is driving the need for stream processing tools that work within the architectural ...
PDF | The use of real-time data streams in data-driven computational science is driving the need for stream processing tools that work within the.
The use of real-time data streams in data-driven compu- tational science is driving the need for stream processing tools that work within the architectural ...
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Abstract—The use of real-time data streams in data-driven computational science is driving the need for stream processing.
The use of real-time data streams in data-driven computational science is driving the need for stream processing tools that work within the architectural ...
The use of real-time data streams in data-driven computational science is driving the need for stream processing tools that work within the architectural ...
Real-time data stream processing technologies play an important role in enabling time-critical decision making in many applications.
Jul 5, 2024 · Stream processing is a technique that helps analyze and process large amounts of real-time data as it flows in from various sources.
Stream processing is the processing of data in motion, or in other words, computing on data directly as it is produced or received. The majority of data are ...
Oct 25, 2023 · Stream processing can be expensive, as it requires high-performance computing resources to process large volumes of data in real time.