The Change Data Capture Best Practices That Will Keep You Ahead of the Curve

When dealing with databases at scale, it can be hard to keep track of changes to the contents. Change data capture (CDC) is a software mechanism to detect and act on changes in a database. The process tracks data throughout a database through complex software. This type of data capture is more innovative and insightful as it works in real-time to provide you with updates to data as changes occur. 

Following industry best practices for change data capture is one of the best ways to get ahead in data analysis. Keeping track of changes is essential for solid database management to ensure that no unauthorized changes are made and that all authorized changes process successfully. 

Narrow Down Your Type of Change Data Capture

There are three types of change data capture methods to choose from. Whichever one you decide to go with depends on your goals and capabilities. 

Log-Based Change Data Capture 

Log-based change data capture method is the automatic implementation of data to be moved at a later time. Log-based change data capture is the most efficient way to log change data. 

Query-Based Change Data Capture 

As its name suggests, query-based change data capture involves you querying the data to alert any new changes. This method is a bit more involved because you must enter timestamps within the data. 

Trigger-Based Change Data Capture  

For trigger-based change data captures, you must assign a trigger to the source application. I would not recommend this method because it can slow the performance of your database. 

Reverse Engineer Requests

If you can capture the inbound traffic that comes through your database, reverse engineer the application requests to see where they came from and provide further analysis. This can help identify and categorize any engineer requests.

Use Dual Writes in the Applications

This process allows you to document the list of changes made automatically within the application. Be careful when using this method, though, because unless you know the code inside and out, it can be easy to make errors. The risk is high if you do not have the source code in case a reversion is needed. As the dual writing method is complex and time-consuming, it should only be performed by analysts with considerable experience with the application. 

Use a Transaction Log 

Processing using a transaction log can be tricky but worth it. Its asynchronous process uses a transaction log to bounce back from any failed transaction to protect your data. Additionally, transaction logs are used for fraud analysis. 

Run a Query

Periodic SQL queries can allow you to quickly and effectively identify change. Regular SQL queries are ideal for backups by using methods such as timestamps. The only downside of periodic queries is that the changes they identify might not be as precise as other methods. 

Use Triggers to Log Change

If you have strong coding experience, using database triggers is an intelligent way to track changes within a table. It should capture any changes and doesn’t require you to update the application as a whole. Be careful with this method; it could slow down your system in the long run and cause system failure if not carefully monitored. 

Snapshot Based 

This comparative technique examines your complete data set side-by-side using a snippet from the staging area within your source table captured at two different times. Use this method for comparing data.

Replication

Database replication copies data from one database to another server. It is a quick method of sharing information to prevent any inconsistencies. Database replication also affords greater leeway when making changes if the original database is maintained as a backup.

Benefits of Change Data Capture 

Using a log-based process includes many benefits that can help identify various data sets, such as: 

• Being non-intrusive
• Being asynchronous 
• Being universally applicable
• Flexibility to work with large systems 

Wrapping It Up 

Change data capture best practices depends on you and your organization’s goals. Implementing reverse engineering, transaction logs, dual writing, queries, triggers, and snapshots will improve your processes and overall efficiency. Just be sure you are confident in your practices and strive to stay ahead of the curve in training and professional development.