This post will take you through the many aspects of the Microsoft SQL Server Change Data Capture (CDC) with a focus on its features and functions. The CDC feature is accessible to users of both the Microsoft SQL Server and the cloud-based Microsoft Azure SQL Managed Instance.
Why is the CDC feature important?
Almost all businesses regardless of their size or structure are dependent on data to power their operations. This means that data security, safety, and durability have to be an integral part of their IT infrastructure. In this context, the Change Data Capture feature has a critical role to play. It ensures that data is stored in systems in a way that does not compromise its value and history, thereby effectively firewalling it from hackers. In the past, many solutions have been tested to insulate data including tools such as timestamps, complex queries, data auditing, and triggers, but none had the desired success.
The Development of Microsoft SQL Server CDC
It was not until the development and launch of SQL Server CDC by Microsoft in 2005 that an attempt was made to resolve the issue. Even though this product had all the required “after update”, “after insert”, and “after delete” features, DBAs found working with it very complex and tedious and hence did not receive it well.
However, when Microsoft introduced a modified version of the SQL Server CDC in 2008, it met all the requirements of the DBAs. They could now directly capture and archive historical data without having to go through any other redundant activities. Because of its user-friendly attributes, this form of SQL Server CDC became very popular and is still the most-preferred tool in this niche.
How does SQL Server CDC work?
The SQL Server CDC feature works on the SQL Server to record changes such as insert, update, and delete and make it available to users in an easy-to-understand and simple relational format. The inputs that are required to capture changes in the target database like column information and metadata are also available for the changed and modified rows. These changes are then marked in tables that have the same column structure as the tracked stored tables. Access to the changes made to the data is controlled stringently through table-valued functions.
For an example of SQL Server CDC, check out the functioning of the ETL (Extract, Transform, Load) application that migrates the incremental and modified data to a data warehouse from the source tables present in the SQL Server.
Why does the SQL Server CDC have an edge over others in this field? It is primarily because of its technologically advanced and cutting-edge features. For instance, in the past, and in some CDC forms even now, users have to continually refresh the source table in a data storage repository that copies the changes made in them, making it a long-drawn-out process. The SQL Server CDC technology, on the other hand, makes sure that change data flows seamlessly from the source and users can apply it to any target as required.
The CDC activity in the SQL Server
The Change Data Capture tool of the SQL Server tracks and monitors all changes made to tables which are then stored in relational tables and can be accessed quickly with T-SQL. In every instance where CDC is applied to a table in a database, a replicated image is available of the tracked table.
Additionally, the type of changes made in the database row is identified by metadata columns present in the architecture of the copied table. Except for this slight difference, all other aspects of the source and the target storage repositories are the same in every respect. DBAs can use the new audit tables for monitoring the logged tables once the SQL Server CDC activity is completed.
The transaction log of the CDC shows the basis of changes made to the source database. As soon as any change is identified in the tracked source tables, it is automatically added to the log with the details of the change and replicated in the change table portion of the original table.
Forms of SQL Server CDC
The SQL Server CDC is available in two forms and businesses typically use the first one before attempting the other.
- Log-based CDC: In this form of CDC, changes made to the data at the source are tracked by the system via the transaction log and file of a database and then replicated in the target database. The main plus point of this process is that it is very reliable and records all changes made. It also does not hurt the functioning of the production database system whose schemas need not be changed or added to new tables.
On the flip side, the drawback is that it is a complex function and can only be used with databases that are compatible with log-based CDC only.
- Trigger-based CDC: Here, the cost of extracting changes is substantially low as triggers placed in the database are automatically set off whenever a change is identified. However, because more system runtime is required as the database has to be repeatedly refreshed, the system maintenance expenses are more.
The main benefits of this trigger-based SQL Server CDC include easier implementation, availability of detailed logs of all transactions through shadow tables, direct support to SQL API for certain databases, and faster changes.
There are some downsides too of this process. Triggers might get disabled when operations are more and the database performance may be impacted because of multiple writes to a database that occurs when changes are made to the rows.
The form of SQL Server CDC used depends on the specific needs of businesses.