What is the difference between batch processing and real-time processing in big data applications?
What is the difference between batch processing and real-time processing in big data applications?
30828-May-2023
Updated on 29-May-2023
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What is the difference between batch processing and real-time processing in big data applications?
Aryan Kumar
29-May-2023Batch processing and real-time processing are two different approaches to handling data in big data applications. Here's an explanation of their differences:
Batch Processing: Batch processing refers to the processing of data in large volumes or batches, typically performed periodically or at scheduled intervals. In this approach, data is collected over a period of time and stored for subsequent processing. The data is processed as a batch, meaning that it is processed as a whole, without immediate or real-time interaction.
Characteristics of batch processing include:
Characteristics of real-time processing include:
While batch processing offers the advantage of handling large volumes of data efficiently, real-time processing provides timely insights and enables immediate actions based on incoming data. The choice between batch processing and real-time processing depends on the specific use case, data requirements, latency requirements, and the desired outcomes of the data processing and analysis. In some cases, a combination of both approaches may be used to leverage the strengths of each for different aspects of the data analysis pipeline.