Comparing Batch Processing and Stream Processing
Having a lot of choices can certainly feel overwhelming in some circumstances. For instance, many IT decision makers have a hard time choosing between batch processing and stream processing. The one thing today’s enterprises don’t have a choice about is taking cyber security seriously. The rise in security breaches in recent months proves that data is always at risk of being stolen or compromised. Even the high-tech efforts by major credit cards and financial institutions aren’t guaranteed to stop fraud. This places a lot of pressure on the shoulders of smaller vendors, businesses and enterprises that handle personal information. The good news is that batch processing and stream processing can make it easier to collect, store and protect data. Taking a few minutes to learn about the key features of both processing types can help you to get a clearer picture of your options. You can then determine which option works best for the goal you’re hoping to achieve regarding your enterprise’s data assets. It’s time to discover how batch processing and stream processing can help you do more with data.
A Look at Batch Processing
While batch processing can cover some pretty complex tasks, it is essentially a very simple process to understand. Batch processing is the execution of a series of jobs without any manual intervention. Jobs can be securely stored during working hours and executed at later times. Batch processing gained popularity because of the fact that it is extremely efficient when it comes to accurately processing data in large volumes. The other important thing to know about batch processing is that it’s especially useful in scenarios that require data to be processed within a small window of time. Batch processing requires separate programs for input, process and output to produce batch results. What does this look like in a real-world application? A basic example would be the way a credit card company processes a customer’s billing activity. A customer will receive one statement that itemizes an entire month of spending instead of individual statements for purchases. This same concept can be applied to a number of internal and external reporting needs for enterprises.
A Look at Stream Processing
Stream processing is something that is really changing the game in the tech world. The reality is that stream processing may not be an ideal solution for every data-related goal you have. However, it can create unprecedented insight and efficiency when it is applied in the right situations. Stream processing is a great platform for processing heavy streams of data. In fact, this type of processing essentially captures data in motion because it is able to act on a real-time basis by constantly calculating analytics within a stream. You can customize your processing mode to catch peculiar events that indicate security breaches, breaks in protocol or system errors. Stream processing can also be used for real-time decision making based on the real-time actions, trends and conditions it is tracking through the data that is being caught. Stream processing is popularly used for fraud detection in the finance and healthcare sectors. It can also be customized to be useful for anything from online commerce to network monitoring.
Why Choosing the Right Processing Type Is Important
The fact that Americans are increasingly using mobile devices in all aspects of their lives means that having a platform for collecting data through engagement is more important than ever for brands and organizations. However, the best processing platform in the world won’t do your enterprise any good if it isn’t what you truly need. It’s important to identify and audit your specific data needs before selecting a processing platform. The real question comes down to whether you need a platform that is passive or evolving. You can then engineer a custom platform that handles the volume of data you need to process in any given time period.