With the aid of CockroachDB's Change Data Capture (CDC) capability, you can keep track of database changes and instantly replicate them to other systems. In order to synchronise data between CockroachDB instances or between CockroachDB and other systems, it is intended to do so in a high-performance and low-latency manner.
When data is edited in the database, a stream of change events is generated, and this is how CDC in CockroachDB functions. These change events are subsequently published to a message queue so that other systems can use them to apply the changes instantly. This enables you to maintain system synchronisation across several platforms or to leverage the change stream for different things like data integration, data warehousing, or real-time analytics.
With the help of the Changefeeds feature, you can implement CDC in CockroachDB by building a continuous query that checks a database or set of tables for changes and provides a stream of events that other systems can use. Changefeeds are an effective tool for developing real-time data pipelines and applications because they are extremely effective, scalable, and simple to use.
Here is an example of how to use Changefeeds in CockroachDB to track changes to a table and stream the change events to Apache Kafka:
First, create a table and insert some initial data:
CREATE TABLE users (id INT PRIMARY KEY,name STRING); INSERT INTO users (id, name) VALUES (1, 'Alice'), (2, 'Bob'), (3, 'Charlie');
Next, create a Changefeed to track changes to the users table and stream the change events to Kafka:
CREATE CHANGEFEED FOR TABLE users INTO 'kafka://host:port' WITH updated, resolved;
This will create a continuous query that monitors the users table for changes and generates a stream of events that are published to the users topic in Kafka.
To test the Changefeed, you can make some changes to the users table and see the resulting change events in Kafka:
UPDATE users SET name = 'Alice Smith' WHERE id = 1;
You can use a Kafka consumer to read the change events from the users topic and process them in real-time. For example, you can use the following Python code to read the change events from Kafka and print them to the console:
from kafka import KafkaConsumer consumer = KafkaConsumer('users', bootstrap_servers=['localhost:9092']) for message in consumer: print(message.value)
You can also use the INSERT, UPDATE, and DELETE statements to modify the data in the users table and see the resulting change events in Kafka.
You can stop the Changefeed at any time by using the DROP CHANGEFEED statement:
DROP CHANGEFEED FOR TABLE users;
This will stop the continuous query and the Changefeed will no longer generate any change events.
In conclusion, CockroachDB's Changefeeds tool is a helpful one that lets you keep track of database changes and instantly replicate them to other systems. It is implemented via continuous queries, which keep an eye on tables for modifications and produce a stream of events that other systems can use.
Changefeeds are an effective tool for developing real-time data pipelines and applications because they are extremely effective, scalable, and simple to use. Data synchronisation between CockroachDB instances as well as between CockroachDB and other systems like Apache Kafka, Amazon Kinesis, or Google Cloud Pub/Sub can be done via Changefeeds.
Changefeeds can be used in a variety of situations to keep systems in sync and enable real-time data processing and analysis. It is a useful tool for developing real-time data pipelines and applications with CockroachDB.