Change Data Capture for Live Data Feeds
Learn how Change Data Capture (CDC) turns database mutations into a real-time event stream that powers live dashboards, caches, and downstream services.
Change Data Capture for Live Data Feeds is a free Real-Time Streaming Systems (WebRTC + Live Data) lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Real-Time Streaming Systems (WebRTC + Live Data) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
What Is Change Data Capture?
Change Data Capture (CDC) watches a database for inserts, updates, and deletes and emits each change as an event.
Instead of polling tables, downstream systems subscribe to the change stream and react in real time.
Why Not Just Poll?
Polling a table every few seconds is wasteful and laggy. It misses fast intermediate states and hammers the database.
CDC captures every committed change exactly once, with low latency and no extra query load.
Reading the Transaction Log
Most CDC tools tail the database's write-ahead log (WAL in Postgres, binlog in MySQL). The log already records every committed change, so reading it is cheap and accurate.
Anatomy of a Change Event
A CDC event typically carries the operation type, the table, and the before/after row state.
{
"op": "update",
"table": "orders",
"before": { "status": "pending" },
"after": { "status": "shipped" },
"ts": 1717000000
}CDC Meets the Message Queue
CDC events are usually published to a stream like Kafka or Redpanda. Each table often maps to its own topic, letting many consumers fan out from one source of truth.
Driving a Live Dashboard
A consumer reads CDC events and pushes updates to clients over WebSocket or SSE. The dashboard reflects database changes within milliseconds, without the UI polling at all.
consumer.on('message', (evt) => {
if (evt.table === 'orders') {
broadcast({ type: 'order_update', data: evt.after });
}
});Keeping Caches Fresh
CDC is ideal for cache invalidation. When a row changes, the event tells your cache exactly what to refresh or evict, so stale data never lingers.
Exactly-Once vs At-Least-Once
CDC pipelines usually guarantee at-least-once delivery, so duplicates can occur on retry. Make consumers idempotent, using the primary key plus a log offset to dedupe.
Snapshots and Backfill
When a new consumer starts, it needs the current state, not just future changes. CDC tools take an initial snapshot of existing rows, then switch to streaming the log.
Popular CDC Tools
- Debezium for Postgres, MySQL, MongoDB into Kafka.
- Postgres logical replication with custom consumers.
- Managed options in many cloud data platforms.
Watch the Schema
When a table's schema changes, downstream consumers must adapt. Use a schema registry and versioned events so a new column does not break existing readers.
Quick Check
Test your understanding of CDC.
Recap
CDC turns database mutations into a real-time event stream by reading the transaction log. Pair it with a message queue to power live dashboards, fresh caches, and reactive services. Make consumers idempotent and handle snapshots plus schema evolution.
Frequently asked questions
Is the “Change Data Capture for Live Data Feeds” lesson free?
Yes — the full text of “Change Data Capture for Live Data Feeds” is free to read here on the web, and the Real-Time Streaming Systems (WebRTC + Live Data) course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Real-Time Streaming Systems (WebRTC + Live Data) course, upgrade to CoddyKit PRO.
What will I learn in “Change Data Capture for Live Data Feeds”?
Learn how Change Data Capture (CDC) turns database mutations into a real-time event stream that powers live dashboards, caches, and downstream services. You practise Real-Time Streaming Systems (WebRTC + Live Data) with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Real-Time Streaming Systems (WebRTC + Live Data)?
No prior experience is required. Real-Time Streaming Systems (WebRTC + Live Data) on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Change Data Capture for Live Data Feeds” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Real-Time Streaming Systems (WebRTC + Live Data) lesson?
Yes. Every Real-Time Streaming Systems (WebRTC + Live Data) lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Message Queues for Event-Driven Systems
- Stream Processing Frameworks
- Real-time Analytics Integration
- Change Data Capture for Live Data Feeds