Change Data Capture (CDC)
Change Data Capture (CDC) is a technique used to track and capture changes in data, such as insertions, updates, and deletions in a transactional database. It is commonly used in data integration, replication, and synchronization to ensure that changes made to source data are accurately reflected in target systems.
Let's look at some applications of Change Data Capture below,
CDC in microservices integration enables near real-time data synchronization between services, allowing them to communicate and stay up-to-date with each other's data changes. This ensures consistency across the entire system and supports event-driven architectures.
CDC can be utilized in audit log capture to track changes in data, such as insertions, updates, and deletions, providing a detailed history of modifications made to a record in a database. This helps maintain data integrity and ensures compliance with regulatory requirements.
CDC in data analytics facilitates real-time data updates, allowing for more accurate and up-to-date data analysis. CDC can help transactional databases like Postgres or MySQL delegate costly analytical computation to OLAP systems like Snowflake, Bigquery and Clickhouse which efficiently support analytical processing via CDC.
CDC in full-text search allows for real-time indexing and updating of the search index, ensuring that search results are always up-to-date and relevant. Synchronizing data from a transactional database like Postgres or MySQL to Elasticsearch via CDC provides efficient up-to-date search results.
In conclusion, CDC based applications enhance data synchronization, maintain compliance, improve data analytics, and provide up-to-date search results, making it a valuable technique for various use cases.
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