Confluent vs. Drools

If you have a need to stream data, real time or segmented structured data then Confluent is a great platform to do so with. You won't run into packet transfer size limitations that other platforms have. Flexibility in on-prem, cloud, and managed cloud offerings makes it very flexible no matter how you choose to implement.

Incentivized

As an open source rule engine and product suite, Drools is well suited for the small and middle scale business to manage and integrate the rules to build the rule-driven system which can process the business-critical data and events to produce the automated decision. It is better to use Drools in the well-secured environment (back-end behind the DMZ), not putting it on the customer-facing front or exposing it directly the to public where may bring direct security risk in the enterprise environment. Drools still needs a lot hardening on the security side.

Incentivized

• Products work great.
• Training is available.
• Customer support is good.

Incentivized

• Writing rules with business focus
• Rules evolution and maintenance
• separate business logic from program code

Incentivized

• Cloud based Azure platform features for Confluent lacks behind AWS And GCP

Incentivized

• Fusion doesn't support persistence of working memory, which brings some extra high availability risk to our business.
• Guvnor still has a lot room to be implemented, it is not so user-friendly for non-technical people, so a lot of business users complain it is hard to master.
• Rule execution server doesn't even have JMX implemented, hard to be monitored.
• Drools is still lacking support for key Web services standards.

Incentivized

The support from the Confluent platform is great and satisfying. We have been working with Confluent for more than a year now. They sent out resident architects to help us set up Confluent cluster on our cloud and help us troubleshoot problems we have encountered. Overall, it has been a great experience working with the Confluent Platform.

Incentivized

For our use case it was very important that the technology we were working with fit into our Azure architecture, and met our data processing size requirements to stream data within certain SLAs. Confluent more than met our performance requirements and compared to the others scale options and cost to run it was more than financially viable as a platform solution to our global operations.

Incentivized

I did not participate in drools choice. I can only compare drools with the previous situation which was using nothing.

Incentivized

• It enables us to develop event driven application.
• It increases our ability to handle streaming data.
• It reduces latency of communication.

Incentivized

• The IT department quickly adopted Drools as it is a very good java-based rule engine, which saves a lot of time to meet the project timeline and balanced our business requirements.
• Recently we start considering the OpenRules, which may be more business user-friendly.

Incentivized