Difference between Batch Processing and Stream Processing

Computer systems have been handling data since decades, but the volume and speed of handling has become phenomenal in the last few years. Data processing means "the collection and manipulation of items of data to produce meaningful information", has been evolving in terms of speed, efficiency, and leveraging the computing resources.

In this article, we will see two important techniques of data processing in the field of computation ? Batch processing and Stream processing. We will elaborate them in detail and see how they are different.

What is Batch Processing?

Batch processing is a technique of processing large amounts of data of repetitive type that does not need human intervention to process. The data is collected over time and processed as a group or "batch" at scheduled intervals.

Batch processes are automatic. Human intervention is minimal in batch processing; it is not required except at the time of submitting the batch until the batch processing is complete. Batch processing is executed on finding idle system time, in the background, at a scheduled time such as after-office hours or overnight, or on demand-basis.

Advantages of Batch Processing

• Cost Savings ? No need of hiring data-entry clerks hence saving on operational and labor costs.

• Optimum Utilization of Resources ? Since batch processing can be handled without hampering the primary tasks of computation in an organization. Batch processing doesn't require anything out of the processing software hence the processing resources are used at optimum.

• Hands-free Managerial Control ? The managers don't need to worry about completion of batches as the software sends exception notifications to appropriate person in case any problem. Once the software is set properly, there is nothing much required to be done.

• Accuracy ? Due to its automated nature, batch processing avoids data errors completely.

Challenges in Batch Processing

• Difficult troubleshooting ? Debugging and troubleshooting of batch processing needs expert professionals having domain knowledge.

• Training costs ? Businesses need to invest in personnel training on batch processing software. The initial investment on training is high.

Usage of Batch Processing

Batch processing can be effectively used to process large amounts of data when processing is required. It is used to ?

• Generate employee payroll data for a month

• Execute bank transactions done over a week's time

• Generate periodic reports

• Generate credit card transactions on monthly basis

• Generate annual financial reports of an organization

• In highly complex computing environments, researchers can submit batches of complex calculations related to science

What is Stream Processing?

Stream processing is a technique in which a continuous stream of data is processed for immediate use, or for analyzing, filtering, combining, or modifying rapidly. The data is typically acted upon when it was created. The continual influx of data is termed as the "data stream". Stream processing involves three stages namely, data acquisition, data processing, and data delivery.

Advantages of Stream Processing

The most prominent advantage of stream processing is that there is no latency. In stream processing, data is fed to the streaming software in very small chunks or "micro-batches". Hence the data analysis can be done in nearly-real-time streaming and the insights are available almost immediately. This feature of streaming enables the businesses to make quick decisions.

Challenges in Stream Processing

• Alignment of streaming software and hardware ? As streaming requires high amount of data to handle, the streaming software and the hardware need to be attuned.

• Speed of execution ? If data influx is slow, the performance of a streaming software can get volatile.

Usage of Stream Processing

Stream processing is inevitable where a continual data ingestion is required, such as ?

• Air-traffic information
• Digital product's user experience (UX) monitoring
• Weather forecasting
• Mapping of customers' journey
• Stock market trading
• Fraud detection
• Flood detection
• Cybersecurity

Differences between Batch and Stream Processing

Batch and stream processing techniques are different in the following ways ?

Conclusion

Batch and stream processing are types of data processing in the domain of computation, each with its own strengths and use cases. Companies can benefit by choosing the right mix of batch and stream processing based on their operational needs and data processing requirements.