Real-time event stream processing, or just “event processing”, refers to a particular, advanced kind of data stream management. To put it simply, information that is being transferred no longer needs to be stored and then processed; instead, it can now be analyzed even while it is in process of being transferred.
In general, event processing is used to analyze data for common aspects or events. Information from multiple sources is combined, matched, analyzed and acted upon.
With a database, data needs to be indexed and saved, possibly even backed up before a query could be made and results are produced. Event stream processing postpones the storage of the information and skips right to the processing. It’s just as effective as previous methods; however, it’s ultra-low latency and high processing rate makes it a new favorite.
Be it generating sales leads, processing orders, or directing customer and internal communication, all of this can now be done much more quickly and cost efficiently.
At GigaSpaces, our in-memory computing platform XAP, utilizes template matching and SQL queries to process data streams. Data from various sources is put in and processed in real time with no delay, no wait—just immediate results—and put out in the form of messaging.
We offer the perfect solution to process complex workflows and simplify the processing. Compared to conventional methods, event stream processing is not only more resource and cost-efficient, but also, saves valuable time when generating relevant and appropriate results for your business.
XAPs’ unit of work combines business logic that is co-located with the data, enabling advanced parallel processing patterns as well as full messaging semantics (p2p or pub-sub) while ensuring consistency through transactions.
Event stream processing is already being used in more and more areas, including trading, fraud detection, computer security, and even e-commerce. Anywhere large amounts of data are moving to or from, this type of processing can be found nowadays, replacing the previous, more static database model. A typical example that demonstrates these concepts is explained in our Services and Best practices section.
With event stream processing, the advantages are clear—it’s faster, more efficient, can deal with more varied types of data, and the outputs can be both processed on or used as a final product. The combination of these factors makes event stream processing an ideal solution for all businesses—including yours!