Amazon Kinesis vs. IBM Decision Manager Open Edition

Amazon Kinesis is a great replacement for Kafka and it works better whenever the components of the solution are AWS based. Best if extended fan-out is not required, but still price-performance ratio is very good for simplifying maintenance.

I would go with a different option if the systems to be connected are legacy, for instance in the case of traditional messaging clients.

Incentivized

Red Hat Decision Manager is well suited for developing a microservices-based application architecture where reusable components / APIs can be used across different end-user applications. It however may not be well suited for use cases where business users need low code / no-code environment to maintain business rules themselves without any developer / IT team support

Incentivized

• Processing huge loads of data
• Integrating well with IoT Platform on Amazon
• Integration with overall AWS Ecosystem
• Scalability

Incentivized

• Business rule management for filtering the candidate
• Automate the possible decision making which reduces the time and increase the productivity
• Whenever business rule changes based on the client requirement.

Incentivized

• Not a queue system, so little visibility into "backlog" if there is any
• Confusing terminology to make sure events aren't missed
• Sometimes didn't seem to trigger Lambda functions, or dropped events when a lot came in

Incentivized

• It should be easy to use because it needs more knowledge
• You should be trained to your partner well
• Well Documentations are needed

Incentivized

Red Hat Decision Manager can be scaled and adapted to meet the automation needs of the organization as it grows by reusing the components and business rules data which provides a high ROI on the renewal costs.

Incentivized

Implementation phase is very difficult .Of course ,you need to know bunch of things about cloud,container,automatization

Incentivized

The documentation was confusing and lacked examples. The streams suddenly stopped working with no explanation and there was no information in the logs. All these were more difficult when dealing with enhanced fan-out. In fact, we were about to abort the usage of Kinesis due to a misunderstanding with enhanced fan-out.

Incentivized

The support for Red Hat decision Manager can be improved to be more omnichannel with better response times for the customers.

Incentivized

For high volume and / or complex set of legacy business rules, plan for adequate time for data migration activities.

Incentivized

The main benefit was around set up - incredibly easy to just start using Kinesis. Kinesis is a real-time data processing platform, while Kafka is more of a message queue system. If you only need a message queue from a limited source, Kafka may do the job. More complex use cases, with low latency, higher volume of data, real time decisions and integration with multiple sources and destination at a decent price, Kinesis is better.

Incentivized

If you have a low budget to invest probably JBoss BRMS is the option for you, if your budget is not restricted you'll probably like to consider Bizagi

• Caused us to need to re-engineer some basic re-try logic
• Caused us to drop some content without knowing it
• Made monitoring much more difficult
• We eventually switched back to SQS because Kinesis is not the same as a Queue system

Incentivized

• Quickly write business rules
• Computers can take decision
• Complex event processing

Incentivized