IBM Decision Manager Open Edition vs. SMARTS Decision Management Platform

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

Smarts is well-suited to handle rules orchestration for complex decision flows where there's a need for advanced functionality and reusable components or assets. It is very useful for scenario testing, modeling, and dashboarding. These capabilities give you robust insights and help you optimize your decisions. It is less appropriate for very simple decisioning needs.

• 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

• 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 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

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

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

Incentivized