July 2, 2008

Event processing vs. data-driven processing

Marco Seiriö offers a distinction between event processing and data-driven processing. Specifically, he says that if an event has an ID, then it’s true event processing; if it doesn’t, and what you’re doing looks somewhat like event processing anyway, then you’re doing data-driven processing.

He seems to believe this is an important distinction, but I’m not convinced yet. Rather, I think the essence of (complex) event/stream processing lies in its performance for certain kinds of data processing problems, some of which require super-low-latency and some of which don’t.

Maybe there’s some kind of a partition of the problem space, in which if you want event IDs you’re better off with an Apama-like rules-engine paradigm, while if you don’t need them you do better with Coral8/Streambase-style SQL. But off the top of my head, I don’t see it.

Am I missing something?


Leave a Reply

Feed: DBMS (database management system), DW (data warehousing), BI (business intelligence), and analytics technology Subscribe to the Monash Research feed via RSS or email:


Search our blogs and white papers

Monash Research blogs

User consulting

Building a short list? Refining your strategic plan? We can help.

Vendor advisory

We tell vendors what's happening -- and, more important, what they should do about it.

Monash Research highlights

Learn about white papers, webcasts, and blog highlights, by RSS or email.