Event Sourcing Is Not for Everyone
14 days ago
- #Event Sourcing
- #Business Events
- #Data Processing
- Event Sourcing is not suitable for all types of data, especially raw data like GPS coordinates or temperature readings.
- Business events, such as 'DriverApproachingPickupLocation' or 'TemperatureThresholdExceeded', have inherent business meaning and consequences.
- Raw data becomes meaningful events only when interpreted within a business context.
- A litmus test for distinguishing events from raw data: 'Would anyone want to be notified about this specific occurrence?'
- Event Sourcing excels when history and auditability are important, such as in banking or healthcare.
- Event Sourcing is not appropriate for high-volume, low-meaning data like access logs or static reference data.
- Architectural separation is key: process raw data to extract meaningful events before storing them in an event-sourced system.
- Event Sourcing is about modeling business-relevant facts, not handling high volumes of incoming data.
- Choosing the right tool depends on whether the data represents business facts or just raw measurements.