This question comes up quite frequently and the short answer is yes – absolutely. To get to the underlying concern behind the question though takes a bit more explanation. It’s a topic we love to talk about at DECISIONS as this is an area of the product that really shines. We look forward to opportunities where we are pitted against our competition to show just how scalable DECISIONS can be.

To begin, DECISIONS can scale vertically simply by applying more hardware. With that said, we can do an awful lot of processing on typical server sizes without having to resort to larger hardware. In fact, most all of our SaaS based clients are running servers of 4 cores and 16GB of memory and are running very low utilization rates. View benchmark data on running on the hardware just mentioned. If you look into the business rule and workflow executions per second, I think you will agree that DECISIONS can handle very high loads.

DECISIONS can also scale horizontally, and run in clusters behind a load balancer. We have a number of customers running clusters of 2-4 servers both for high transaction rate processes and for highly available, mission critical applications.

Finally, as of our latest version 6.0 we now support Docker containers. If you have a batch job running weekly that is truly hardcore – no worries. We can spin that off to one or more docker containers and shut those down when completed. So, there is truly no limit to how high DECISIONS can scale.

Cool customer applications? We’ve got those too. We have worked with an IOT client and tested an implementation running over 20,000 messages per second on a single server. We’ve got customers with over 300,000 users and others running several thousand concurrent users. We are even involved in real-time credit card applications with under 50 millisecond response rates. So, if it’s scale that you are worried about – yes, DECISIONS can scale.

If you have any questions, please reach back to us at sales@decisions.com or request a demo. We’d love to talk to you about scaling applications.