The Power of Change Data Capture: Real-Time Data Integration

The Importance of Change Data Capture in Modern Business

Modern businesses are increasingly data-driven. In the Big Data age, data is a valuable asset that fuels digital transformation and decision-making. However, data‘s value has a short lifespan; insights can quickly become outdated. To remain valuable, data must be current. This is where Change Data Capture (CDC) comes in.

CDC ensures that multiple systems accurately reflect changes in the target system, keeping data up-to-date and relevant.

What is Change Data Capture?

CDC is an improved form of traditional ETL/ELT practices. Its adoption has grown as businesses grapple with managing increasing volumes of data and systems. CDC allows users to detect and manage incremental changes at the data source as they occur. This requires fewer resources than full data loads. Additionally, real-time changes enable better analysis and decision-making, while reducing time and costs.

Why Your Business Needs CDC

CDC adoption is rapidly growing due to its numerous benefits:

• Real-time Data Transfer: CDC enables real-time data transfer, crucial for businesses operating 24/7. This also increases the scalability of the solution.
• Accurate and Up-to-Date Data: CDC provides accurate, current data, essential for businesses to improve agility, flexibility, and customer orientation. It also helps identify trends and patterns, enhancing data-driven decisions.
• Efficient Data Replication: CDC allows for the separation of operational data from analytical data, or the replication of on-premise environments to the cloud.
• Improved Resource Management: CDC replaces batch processing, freeing up resources and computing power.
• Enhanced System Integration: CDC helps integrate disparate systems, improving collaboration between departments.
• Improved Data Quality: By capturing changes at the transaction level, CDC enhances data quality and reliability across systems.
• Effective Recovery Solution: CDC is ideal for businesses needing a robust recovery solution or for audit and compliance purposes.

How to Implement CDC

Organisations can deploy CDC solutions using various techniques based on their specific needs and performance requirements:

• Audit Columns (Timestamp), also known as Query-Based, by using existing “MODIFIED_AT” or “DATE_MODIFIED” columns, or by adding them, you can create your own solution: you can then retrieve only the rows that are changed based on timestamp.

Example: “SELECT * FROM table

WHERE modified_at > last_timestamp ”

‘’’The result of the query above is what has changed’’’

Pros: easy to implement on any RDBS, doesn’t require external tooling, easy permission structure (read-only)

Cons: performance overhead, latency (is a pull method), doesn’t register deletes.

• Trigger-Based, another method is defining database triggers, and creating a log table (or Audit Table) where every transaction is registered (Insert, Update or Delete).

Example: Tools like PostgreSQL or SQL server, have native stored procedure and views, where all the database changes get registered.

Pros: Immutable, Complete and Detailed logs; Often native features.

Cons: Requires multiple write on operational systems; Not Scalable (each table needs a trigger).

• Log-Based, every transaction is recorded in a transactions log, also 

Example: many vendors like SQL, PostgreSQL or Oracle have native features that write changes to a system log table.

Pros: Fastest and less intrusive solution; full ACID reliability; no need for schema drift or extra tables; perfect for recovery.

Cons: Parsing the internal logging format of a database can be complex, and most database vendors do not document format nor announce updates. Additionally this task often requires third party tools.

Common Use Cases

• E-commerce: Track changes in stock, orders, and prices.
• Marketing and Analytics: Monitor changes in customer preferences, web traffic, and ad campaigns.
• Supply Chain: Synchronise and coordinate different systems, optimise inventory, and plan workloads.
• Financial Industry: Monitor changes in account balances, transaction history, and fraud detection.
• Healthcare: Track patient records, treatments, and medical histories across systems.
• Government/Public Services: Track citizen records, compliance data, and public requests.

Key Takeaways of Change Data Capture

Increased Revenue: Up-to-date data leads to faster, more informed business decisions.

Cost Savings: Incremental data loading reduces the time and processing power required for data ingestion.