Database Polling vs Message Queues
Developers should use database polling in scenarios where systems lack built-in change data capture (CDC) mechanisms or when integrating with legacy databases that do not support triggers or event listeners meets developers should learn and use message queues when building microservices, event-driven architectures, or applications requiring reliable, asynchronous processing, such as order processing in e-commerce or real-time notifications. Here's our take.
Database Polling
Developers should use database polling in scenarios where systems lack built-in change data capture (CDC) mechanisms or when integrating with legacy databases that do not support triggers or event listeners
Database Polling
Nice PickDevelopers should use database polling in scenarios where systems lack built-in change data capture (CDC) mechanisms or when integrating with legacy databases that do not support triggers or event listeners
Pros
- +It is suitable for batch processing, data synchronization between systems, or implementing simple notification systems where low latency is acceptable, such as in cron jobs or background tasks that update dashboards or caches
- +Related to: change-data-capture, database-triggers
Cons
- -Specific tradeoffs depend on your use case
Message Queues
Developers should learn and use message queues when building microservices, event-driven architectures, or applications requiring reliable, asynchronous processing, such as order processing in e-commerce or real-time notifications
Pros
- +They are essential for handling high-throughput scenarios, ensuring data consistency across services, and improving system resilience by isolating failures and enabling retry mechanisms
- +Related to: apache-kafka, rabbitmq
Cons
- -Specific tradeoffs depend on your use case
The Verdict
Use Database Polling if: You want it is suitable for batch processing, data synchronization between systems, or implementing simple notification systems where low latency is acceptable, such as in cron jobs or background tasks that update dashboards or caches and can live with specific tradeoffs depend on your use case.
Use Message Queues if: You prioritize they are essential for handling high-throughput scenarios, ensuring data consistency across services, and improving system resilience by isolating failures and enabling retry mechanisms over what Database Polling offers.
Developers should use database polling in scenarios where systems lack built-in change data capture (CDC) mechanisms or when integrating with legacy databases that do not support triggers or event listeners
Disagree with our pick? nice@nicepick.dev