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.

Data processing in data engineering can be defined in layman’s terms as the manipulation, transformation, and analysis of raw data which is done to extract the meaningful information. This provides ease in decision-making. Various types of data processing techniques are used to process data, like, ELT, data streaming, warehousing, batch processing, ML algorithms, etc.

Batch processing is a method that computers use to run high-volume repetitive data jobs.

• It allows users to process data when computing resources are available, and with little or no user interaction. Jobs are software programs. Batch size is the number of work units to be processed within one batch operation.
• Users collect and store data, then process the data during an event known as a batch window. Apart from submitting jobs and collecting the data, no other interaction is required to process batch as they run automatically at scheduled times and based on the availability of resources.
• Large amounts of data can be efficiently managed using the batch processing specifically those, that need frequent or repetitive tasks.

Some examples of Batch processing jobs are:

• Data conversion
• Supply chain fulfillment
• Report generation
• Billing and payroll
• Inventory processing
• Maintaining subscription cycles

Batch processing can be used in cases like financial service providing organizations, Research and scientific work and software as a service.

Advantages of Batch Processing

• Increases efficiency as it is ideal for processing large volumes of data in batches rather than doing it individually
• Can be done during less-busy designated time independently
• Is cost effective

Disadvantages of Batch Processing

• Sometimes the one time process in batch processing can be very slow.
• There is time delay between collection of data(receiving the transaction) and getting result(the output in master file) immediately after that.

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

Following are the differences between Batch processing and Real-time processing:

Batch processing is complex in computation and is more cost effective, while real-time processing can be costly due to the equipment but delivers specific and predictable outputs. As per requirement of organization and their input and required output, the type of processing can be chosen.