Getting Reactive with Relational Databases and R2DBC
summary
R2DBC claims full non‑blocking SQL by building on Reactive Streams and the demo proves it: a MariaDB R2DBC driver + Spring Data R2DBC + Project Reactor stack creates connections as r2dbc connection factory returns a Publisher, maps rows via Mono/Flux, and persists rows into a task table. A custom subscriber implements backpressure by requesting 2 items at a time; the demo database contains six tasks and the reactive flow completes successfully with expected onNext/onComplete events.
AI-written summary · about
chapters (16)
- 0:00Introduction
- 1:23Reactive Programming with Databases
- 2:03What is Reactive Programming
- 7:55How can this be done
- 10:36Anatomy of a data stream
- 13:26Reactive Streams API
- 16:24Why is this important
- 18:51What is R2DBC
- 23:42Reactive Streams
- 28:03R2DBC Drivers
- 29:03Connection Configuration
- 32:39Reinvent the Wheel
- 37:39Main Method
- 39:07Maintaining Persistence
- 41:32Inversion of Control
- 44:43Custom Subscriber
related talks
56mGetting Reactive with Relational Databases & R2DBC
34mR2DBC = R2D2 + JDBC (Well, Almost...)
26mBuilding Reactive Application with R2DBC.
37mReactive Relational Database Connectivity using R2DBC
48mReactive Relational Database Connectivity
01h 10mWhy We Decided to Move to R2DBC and How That Ended
49mSpring Data R2DBC. Explaining It One Last Time
50mFull Steam Ahead, R2DBC!