All That You Need To Know About the SQL Server CDC Feature
This post will take you through the various nuances of the Change Data Capture (CDC) feature of the Microsoft SQL Server. We will explore the utility of CDC, how the SQL Server CDC feature evolved to its present form, its functioning, and the different types of Microsoft SQL Server Change Data Capture.
The Utility Of Change Data Capture (CDC)
Most companies around the world, regardless of their size and structure are data-driven in their operations. Hence, it is very critical to have data durability and stringent data security and safety norms in place. Here, Change Data Capture has an important role to play. It ensures that not only data security norms are strictly followed but also that changes made to data are stored in a way that does not compromise their values and history.
Over time, various solutions like timestamps, intricate queries, data auditing, and triggers have been tried out without much success. The breakthrough was achieved when Microsoft launched its SQL Server CDC feature.
The Evolution of Microsoft SQL Server CDC
The first version of SQL Server CDC was launched by Microsoft in 2005 with “after update”, “after insert”, and “after delete” features. However, its functioning was not smooth and seamless and Database Administrators found the technology to be quite cumbersome. Based on the feedback, the company introduced another version of this feature in 2008. This was quite user-friendly and database administrators could capture and store changes made to historical data directly without first carrying out some preparatory activities. This version of the SQL Server is still in use today.
The Technology Behind SQL Server CDC
The main purpose of the SQL Server CDC is to make changes like insert, update, and delete to the database and provide details of them to users in a simple relational format. The inputs needed to capture these changes to the target such as column information and metadata are available for the modified and changed rows. Once the changes are made and recorded in the tables at source, they are replicated in the column information of the target tables, access to which is strictly controlled by table-valued functions.
Comparatively, SQL Server CDC steals a march over the others in the field. Generally, in other forms of CDC technology, it is necessary to refresh at periodical intervals, the source tables in a database to replicate the changes to a target repository. This is not only very time-consuming but also a long-drawn-out process. SQL Server CDC on the other hand provides a continuous stream of change data that can be applied to any table or application that users feel appropriate.
A user instance of the SQL Server CDC is the Extract, Load, and Transform (ETL) application. Here, the changed and incremental data in source tables in the SQL Server is moved to a data warehouse by the ETL application.
The Functioning Of The SQL Server CDC
Change Data Capture tracks and monitors all changes made to tables by users. These changes, which are later stored in relational tables can be easily accessed and retrieved with T-SQL. A replicated image is created of the tracked table whenever the features and capabilities of the Change Data Capture technology are applied to a database table.
Moreover, the format of the changes that are made in the database row is verified by additional columns of metadata existing in the architecture of the replicated table. This is the only point of difference between the source and the replicated tables and all other features of the two are similar. SQL DBAs can access the new audit tables after going through the SQL Server CDC activity for tracking the logged tables.
The transaction log of the SQL Server CDC shows the source of change in the CDC. As soon as any modification occurs in the tracked source tables, all details of the changes are recorded in the log. This log along with the specific content of the changes is now linked to the change table portion of the original table.
The Types of SQL Server CDC
There are two types of SQL Server CDC. Typically, users prefer to start their CDC operations with the first and then go to the second type of CDC.
#Log-based CDC
In log-based SQL Server CDC, all changes made in the database are found in the transaction log and file. These changes made at the source are then replicated to the target database. This method of CDC is very reliable as no changes made are left out from being replicated in the target database. There is no need to add new tables, nor do schemas of the production database have to be changed.
The downside of the log-based CDC is that it is a very complex method and applicable only to databases that support log-based CDC.
#Trigger-based CDC
In this method, the data extraction costs are significantly reduced since the SQL Server CDC is based on triggers that are automatically set off whenever any changes occur in the source system. This cost reduction though is offset by the increased cost of running the source system as the database has to be refreshed every time a change occurs.
The trigger-based SQL Server CDC has several advantages. These include easy implementation, detailed logs of all transactions provided by shadow tables, changes taking place faster, and direct support by SQL API for certain types of databases. The main downside here is the disenabling of triggers sometimes when the load is heavy. Further, multiple writes are required to a database when changes are made to rows, thereby adversely affecting the database performance.
In short, SQL Server CDC has radically transformed the functioning of database systems in organizations for the better.