Projections

Projections in Cratis allow you to create read models from events stored in the event log. They provide different levels of complexity from simple auto-mapping to sophisticated hierarchical models with joins.

Projection recipes

Recipe	Description
Simple projection	Basic projection using AutoMap()
Projection with properties	Explicit property mapping and transformations
Projection with children	Hierarchical data models with child collections
Projection with joins	Cross-stream projections using joins
Projection functions	Mathematical operations and calculations
Projection composite keys	Multi-property key identification
Projection with event context	Using event metadata in projections
Projection with FromEvery	Setting properties for all events in a projection
Projection with initial values	Default values for read model properties
Projection with RemoveWithJoin	Cross-stream child removal
Passive projection	In-memory projections for on-demand lookups
Projection with FromEventSequence	Sourcing events from specific event sequences
Projection with NotRewindable	Forward-only projections that cannot be replayed

Key concepts

Auto-mapping vs explicit mapping

• Auto-mapping: Automatically maps properties with matching names between events and read models
• Explicit mapping: Gives you full control over property transformations and mappings

Event handling

• Projections can handle multiple event types
• Each event type can have its own property mappings
• Properties are updated incrementally as events are processed

Keys and identification

• Event source ID is used as the default key for read models
• Child collections use custom identifiers for individual items
• Joins use keys to link data from different streams

Performance

• Projections are automatically maintained as events are appended
• The system handles indexing and query optimization
• Consider join complexity and update frequency when designing projections