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Imagine you're running an online store. Every second, customers are placing orders, updating their profiles, and adding items to their carts. Now, you need to keep your search engine updated, send order confirmations, and sync data to your analytics dashboard.
Here's a question: How do you keep all these systems in sync?
Option 1: Process the entire database every few minutes to find what changed
Option 2: Only capture and process the data that actually changed
Which sounds smarter? Option 2, right?
That's exactly what Change Data Capture (CDC) does. Instead of scanning through millions of records to find updates, CDC tracks only what changed. Every new order, every profile update, every deletion, as it happens.
Think of it like this: Would you rather read an entire newspaper to find one new article, or get a notification showing you exactly what's new? CDC is that notification system for your database.
Change Data Capture is a technique that tracks three simple things in your database:
Inserts (new data added)
Updates (existing data modified)
Deletes (data removed)
Instead of asking "what does my database look like now?", CDC asks "what just changed?"
Let's say you have a customers table with 1 million records. In the last hour, only 50 customers updated their addresses.
Without CDC: You'd have to scan all 1 million records to find those 50 changes.
With CDC: You instantly know exactly which 50 records changed, what the old values were, and what the new values are.
When someone moves to a new city, CDC captures something like this:
{
"operation": "UPDATE",
"table": "customers",
"before": {
"customer_id": 12345,
"name": "Sarah Mitchell",
"city": "Austin"
},
"after": {
"customer_id": 12345,
"name": "Sarah Mitchell",
"city": "Seattle"
},
"timestamp": "2025-12-19T10:30:00Z"
}
You get the complete picture: what changed, when it changed, and both the old and new values.
You might be wondering, "Okay, but when would I actually need this?" Here are some real-world scenarios where CDC shines:
Maintaining your game progress across devices You're playing a mobile game like Candy Crush. You complete a level on your phone during lunch. Later that evening, you open the game on your tablet, and boom, your progress is right there. CDC captured your level completion and synced it across devices instantly.
Updating live sports scores in real-time You're watching a football match on ESPN's website. Every time a goal is scored, the live scoreboard updates within seconds. CDC captures the score change in the database and pushes it to millions of viewers simultaneously, no page refresh needed.
Tracking every transaction in your bank account Think of your bank statement. Every transaction (withdrawal, deposit, transfer) is logged with exact timestamps and amounts. If there's a dispute, the bank can show you exactly what happened and when. CDC creates this breadcrumb trail automatically for every data change.
Instantly unlocking Netflix after payment You just paid for your Netflix subscription. Within seconds, the "Payment Required" banner disappears and you can start watching shows. CDC captured your payment status change and notified the streaming service instantly, no manual refresh needed.
CDC isn't just one technique. There are different ways to capture changes, each with its own trade-offs. Let's look at the most common approaches:
Most modern cloud data platforms come with built-in CDC capabilities. Let's look at how two popular platforms handle it.
Snowflake uses something called Streams to track changes.
What's a Stream?
Think of it as a change tracker that sits on top of your table. It automatically records every insert, update, and delete without you doing anything special.
How it works:
-- Create a stream on your orders table
CREATE STREAM orders_stream ON TABLE orders;
-- Later, check what changed
SELECT * FROM orders_stream;
When you query the stream, you see only the rows that changed since you last checked. Snowflake even tells you what type of change occurred (insert, update, or delete).
Databricks offers Change Data Feed as part of Delta Lake.
What's Change Data Feed?
It's a feature you enable on Delta tables that tracks all changes automatically. Every modification gets logged, and you can query the history of changes anytime.
How it works:
-- Enable change data feed on a table
ALTER TABLE customers
SET TBLPROPERTIES (delta.enableChangeDataFeed = true);
-- Read all changes since a specific version
SELECT * FROM table_changes('customers', 2, 10);
You can see exactly what changed between any two versions of your table, making it perfect for auditing and incremental processing.
Change Data Capture is like having a notification system for your database. Instead of constantly checking what changed, CDC tells you exactly what happened, when it happened, and what the old and new values were.
Remember the key points:
CDC tracks inserts, updates, and deletes as they happen
Log-based CDC is the most efficient approach for production systems
Modern platforms like Snowflake and Databricks have built-in CDC features
Start simple with triggers or timestamps, then graduate to specialized tools as you scale
Not every use case needs CDC. Sometimes a simple batch job is better
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