Microservices Data Patterns: CQRS & Event Sourcing
summary
Argues that CQRS plus separate read stores is the common practical step toward event sourcing, with concrete trade offs: event sourcing gives very fast writes but slower reads; choose tech by latency, size, update frequency and ownership. Recommends in-memory grids like Infinispan continuous queries for push-based fast reads and local shards, Kafka for durable ordered replay, Vert.x for reactive API caching, and CDC that reads the DB transaction log to emit JSON events. Shows a demo generating events every 200ms and contrasts domain vs low-level event coupling.
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chapters (23)
- 0:00Introduction
- 1:00Migrating to Microsoft Databases
- 2:08Data
- 4:05Data Management
- 4:48Release Cycles
- 6:49Dynamic Domain Model
- 7:29Event Sourcing
- 9:11Event Sourcing Architecture
- 11:46CQRS
- 12:27QQ Operations
- 12:52Secure RS
- 13:19Security Architecture
- 18:43Performance
- 19:22Distribution
- 22:00Use Cases
- 22:47Distributed Secure Stores
- 25:19Events
- 26:02Considerations
- 29:37Memory Data Grids
- 39:19Data Virtualization
- 41:16Message Brokers
- 44:17Reactive Platform
- 47:13Change Data Capture
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