Before going into the various aspects of Microsoft SQL Server Change Data Capture, it is necessary to understand the concept of Change Data Capture (CDC).
In the modern digital environment, most businesses regardless of their size or structure depend on data analysis to run their operations. Hence it is critical for them to ensure not only data durability but also have stringent data safety norms in place.
This is where Change Data Capture steps in by making sure that data safety norms are in place while storing data so that their values and history are not compromised. In the past, several attempts had been made to implement these data storage parameters including data auditing, timestamps, triggers, and intricate queries. None of them met the desired levels until Microsoft launched their SQL Server Change Data Capture.
The Evolution of Microsoft SQL Server Change Data Capture
It was in 2005 that Microsoft first ventured into the CDC niche with “after update”, “after insert”, and “after delete” options. However, Database Administrators did not easily adapt to this version as they found it too complex to implement. Being receptive to this feedback, Microsoft launched a modified version in 2008 with cutting-edge features that are still in use today.
The modified version is very user-friendly. DBAs can capture changes made to historical data in a safe and secure environment without the need to configure the databases again.
The function of this Microsoft SQL Server Change Data Capture will now be examined in detail.
How Does Microsoft SQL Server Change Data Capture Work
The main objective of the SQL Server Change Data Capture is to record all changes made in the data like delete, update, or insert. The details of these changes are then provided to the users in a simple relational format. What helps is that the tools required to capture the changes to data such as column information and metadata are available and in-built into the modified and changed rows.
Now, once these changes are captured and recorded in the source tables, the same is replicated under column information in the target tables. However, access to the SQL Server Change Data Capture changes is strictly controlled by the table-valued function to ensure data security.
There are several functionalities of the Microsoft SQL Server Change Data Capture that make it a cut above other technologies in this niche.
For example, other CDC tools require users to continuously refresh the source tables in a database at fixed intervals to capture the changes made at the source in the target database. This makes them complex and time-consuming to work with.
On the other hand, SQL Server Change Data Capture automatically provides continuous data about changes made that can be applied to specific tables or applications whenever needed. The Extract, Load, and Transform (ETL) application is one such example where data changes as well as incremental data is moved from a data warehouse or data mart from source tables.
The changes made by users in tables are monitored by SQL Server CDC and stored in relational tables to be accessed and retrieved through T-SQL whenever needed. When the functions of Change Data Capture are applied to a database table, it triggers a replicated image of the table automatically.
The replicated tables have additional columns of metadata that check for changes made in the database rows. This is the only point of difference between the source and the replicated tables whose architecture is otherwise similar in all respects. This resemblance makes it simpler for users and DBAs to use the SQL Server CDC features to monitor the logged tables and access the new audit tables.
A benefit of the SQL Server Change Data Capture technology is that the source of the changes made is also reflected in the transaction log. All changes made in the tracked source tables are instantly entered in the log and their details are linked to the change data section of the original source table.
Forms of SQL Server Change Data Capture
There are two types of Microsoft SQL Server Change Data Capture – Log-based CDC and Trigger-based CDC. While both are standalone entities, users should implement the first before moving to the second.
Log-based CDC
In this form of SQL Server CDC, all changes made to the source database are entered in a transaction log and the file before being replicated to a target database. This form of CDC is very reliable as all changes made are compulsorily replicated and none can be left out. There is no need to add new tables or change the schemas of the production database.
On the downside of this method of SQL Server CDC, it is only applicable to databases that support log-based CDC.
Trigger-based CDC
In this method of SQL Server CDC, triggers are placed in the source database that are instantly activated whenever a change is tracked. Operational costs are significantly reduced here as human intervention is not required at any stage. However, this savings in costs is offset by the increased run time of the source database as it must be refreshed every time a change takes place.
Trigger-based SQL Server Change Data Capture is comparatively more feature-rich than Log-based CDC. The benefits include easy implementation, provision of detailed logs in shadow tables of all transactions, and direct support from SQL API for certain databases. Additionally, tracking and recording changes made in databases is faster in Trigger-based CDC than in the other.
Trigger-based CDC is not without certain drawbacks. First, the triggers tend to disengage when the load of changes becomes too heavy. Second, there is often a drop in database performance as several writes are required to a database when changes take place in rows.
