Real-time Processing
Real-time processing is a method that computers use to process data at a near instant rate. To do so and maintain the real-time insights, constant flow of data intake and output is required.
Here, data input is processed without any delay and generates immediate output. This feature of real-time processing is useful for online transactions, real-time analytics and sensor data analysis.
Examples:
- Fraud detection systems
- Online transaction processing (e.g., bank ATMs)
- Real-time monitoring systems (e.g., radar systems)
- IoT applications (e.g., temperature sensors)
Advantages of Real-time Processing:
- Continuous data streaming and no significant delay in response
- low latency
- high availability
- immediate data processing enables real time insights, fraud detection, real-time quality control, patient monitoring and so on
Disadvantages of Real-time Processing:
- challenges in ensuring data accuracy
- challenges in managing large volumes of high-velocity data
- expensive and complex type of processing
- need of computational resources, infrastructure and resource allocation
What is the difference between batch processing and real-time processing?
In this article, we will learn about two fundamental methods that govern the flow of information and understand how data gets processed in the digital world. We start with simple definitions of batch processing and real-time processing, and gradually cover the unique characteristics and differences.
Table of Content
- Data processing in Data Engineering
- Batch Processing in Data Engineering
- Real-time Processing
- Difference between Batch processing and Real-time Processing
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