Under the Hood of Reactive Data Access
summary
Explains how true reactive data access requires end-to-end nonblocking drivers and contrasts r2dbc vs ADBA; shows MongoDB’s reactive-streams driver is a facade over an async driver so cursor batching causes many surprising getMore calls when client-side filters drop rows and demonstrates limitRate as a practical fix. Surveys Redis, Couchbase and a reactive bridge over DataStax Cassandra, notes heavy reliance on Netty + Reactor, and warns that calling .block() on event‑loop threads breaks the model and can freeze the app.
AI-written summary · about
chapters (20)
- 0:00Intro
- 1:45Reactive Spring Data Modules
- 3:25Relational Databases
- 6:46Reactive SOL Access
- 10:46Synchronous Data Access
- 11:39Reactive Data Access
- 14:31Differences to imperative Data Access
- 15:48Synchronous Timeouts
- 17:56Reactive Drivers
- 27:42MongoDB Driver Fetching
- 35:59Specific Features
- 37:12Redis
- 38:17Command by Time
- 39:35Specifics
- 41:22Apache Cassandra
- 42:39Query by Time
- 44:12Couchbase
- 46:50Blocking with Imperative Programming
- 47:11Blocking with Reactive Programming
- 48:01Event Loop
related talks
29mReactive Data Access with Spring Data
32mUnder the Hood of Reactive Data Access
26mBuilding Reactive Application with R2DBC.
56mGetting Reactive with Relational Databases & R2DBC
48mGetting Reactive with Relational Databases and R2DBC
01mGetting Reactive with Relational Databases and R2DBC
34mReactive Architecture
48mReactive SQL: why it matters