Microsoft SQL Server Change Data Capture – A Comprehensive Overview

In this post, we will take a comprehensive view of the many facets of the Microsoft SQL Server CDC (Change Data Capture) feature, starting from its launch, how it evolved over time, and its functionalities. At the end, we will examine the types of SQL Server CDC and the pros and cons of each of them.

What is Change Data Capture

Before we dive into the many intricacies of Microsoft SQL Server CDC, let us first understand what Change Data Capture is. 

Most organizations in today’s business ecosystem depend heavily on data to drive their routine operations. Hence, data durability is essential, and stringent security measures must be implemented to protect this data. It is here that Change Data Capture comes in handy for both these points.

Change Data Capture is a software design that ensures that all data in a system are firewalled and secured so that data breaches do not happen and potential hackers are kept away. It also stores data in a way where its values and history are not compromised.

There have been several temporary solutions with these capabilities in the past such as triggers, timestamps, data auditing, and complex queries but none had the desired effect until Microsoft SQL Server CDC came along.

The Launch and Progress of SQL Server CDC

Microsoft was the first to introduce CDC when in 2005, they launched their SQL Server CDC with “after update”, “after insert”, and “after delete” features. Since it was in a rudimentary form, it did not meet the expectations of DBAs who found it complex to work with.

Acting on this feedback, Microsoft came up with another version in 2008 and this SQL Server CDC met with great success. It was possible here to capture and archive historical data without performing any additional activities. This expectedly was well-received by all and this version with all its features is still in use today.

The Functioning of The Microsoft SQL Server CDC

SQL Server CDC uses the SQL Server to capture changes made to a database. These changes including insert, update, and delete are then presented to users in a simple relational format. Further, all inputs like column information and metadata used to capture the changes made to the intended target are available for the modified rows.

All changes made are noted in tables that mirror the architecture of the columns of the tracked tables. In all instances, these changes are strictly firewalled, and access to them is regulated by table-valued functions.

The ETL or Extract, Transform, and Load application is an ideal example of SQL Server CDC assisting the user. The application moves incremental data from the source tables in the SQL Server to a target data warehouse. 

Why is the SQL Server CDC considered a cut above similar software in this niche? To understand it, let us check the CDC process in other systems. There, users have to perform multiple refreshes in source tables in a data storage repository to replicate the changes made in them. On the other hand, SQL Server CDC makes sure that there is an uninterrupted flow of change data that can be used on different platforms as required by users.

The Roadmap Followed by the SQL Server CDC

Any changes made to tables are tracked by the Change Data Capture feature, stored in relational tables, and accessed and retrieved by T-SQL.  When CDC is applied to a database table, a replicated image of the tracked table is created.  

Moreover, the type of changes made in the database row is checked by the added columns of metadata that exist in the structure of the replicated tables. Except for this difference between the source and the replicated tables, both are similar in all other metrics. After carrying out the SQL Server CDC activity of tracking logged tables, DBAs on the job can use the new audit tables. 

The transaction log in the SQL Server CDC reflects the sources of the changes made. Whenever the tracked source tables find any data changes, all their details are noted and added to the log. The specific nature of the changes as shown in the log is then connected to the change table part of the original table.

The Types of Microsoft SQL Server Change Data Capture 

There are two types of SQL Server CDC. It is advisable for organizations to carry out the first method before moving on to the second.

Log-based CDC  

In this type, changes made at the source are identified by the system with the help of the file and transaction log of a database and then replicated in the target database.

Pros: The primary advantage of the log-based SQL Server CDC is that every change is duly recorded. This method is therefore very reliable and does not affect in any way the production database system. There is no need to add new tables nor is there a necessity to change the schemas of the production database.

Cons: This method can be used only with databases that support log-based CDC and is a very complex procedure.

Trigger-based CDC

In this type of SQL Server CDC, triggers placed in the database are automatically set off as soon as a change occurs in the source database. 

Pros: The cost of data extraction is significantly low. Further, it is easy to implement as shadow tables provide detailed logs of the transactions. Additionally, direct support is received in the SQL API for specific databases. Changes take place quickly too.

Cons: Triggers may get disabled when there is an overload of transactions. The performance of the databases is sometimes adversely affected as multiple writes to a database occur when changes are made to the rows.