An Insight Into Microsoft SQL Server Change Data Capture (CDC)


SQL Server CDC (Change Data Capture) uses SQL Server to make changes like insert, update, and delete. The details of the changes can be accessed in a simple relational format. All inputs to capture the changes to a target ecosystem, like metadata and column information, are available for the modified and changed rows.

The changes are captured and stored in tables that mirror the structure of the columns of the tracked stored tables. Necessary table-valued functions control the access to this change data. The SQL Server CDC technology ensures a smooth flow of change data that is structured to help users apply it to various target platforms.  



Types of SQL Server Change Data Capture

There are two types of SQL Server CDC.

Log-based CDC: Here, the transaction log and file of a database are analyzed by the system to know about the changes made at the source. Next, all changes made at the source are replicated to the target database.

The main benefit of this form of SQL Server CDC is that it is very reliable and all changes are included without any being missed. There is also a minimal effect on the production database system. The schemas of the production tables need not be changed, nor is there a need to add new tables. However, the downside is that this method works only with databases that support log-based CDC.  

Trigger-based CDC: Here, triggers are placed in the database that automatically react when any event or change occurs, thereby lowering the cost of extracting the changes. On the other hand, there is an increase in the cost of running the source systems as additional runtime is required every time the database is refreshed.

Summing up, SQL Server CDC is a boost for data-driven organizations.       

 


Comments

Post a Comment

Popular posts from this blog

The Development of the Oracle Change Data Capture Technology

Image
  Oracle CDC ( Change Data Capture) was first launched by the company as a built-in tool in Oracle databases along with its 9i version. It was to record and track changes in the user tables in a database. These changes were stored in change tables to be later processed and transferred to other data warehouses and databases.  The first version of this technology had triggers placed in source databases and was not widely accepted, as it was considered too invasive. Based on this feedback from users, Oracle brought a change to the Oracle CDC , named it Oracle Streams, and released it with the 10g version.   The second version, named Oracle Streams, was more refined and widely accepted. It used the redo logs of the source database in combination with an in-built replication tool of Oracle Streams. Thus, any change was quickly noticed, with the change data being moved to a target data repository without affecting the performance or speed of the source database. What gave this...
Read more

How to Optimize Oracle on Amazon S3 Platform

Image
  Oracle is a proprietary relational database management system (RDMS). It is primarily used for Online Transaction Processing (OLTP) and data warehousing. Most applications, such as GNU/LINUX and Windows Server, merge easily into the database. Oracle is ACID-compliant, which adds an extra layer of security, data integrity, and reliability to the database. Given these attributes, why would organizations want to move databases from Oracle to S3 , the Simple Storage Service from Amazon? Amazon S3 is a cloud-based data warehousing solution that is ideal for Online Analytical Processing (OLAP). S3 ensures a high level of data availability, scalability, performance, and storage. There are several ways that S3 increases the efficiency of Oracle databases, with the most important being the lowering of payouts to Oracle. It is also wise to move entire databases from Oracle to S3, given the many benefits that such a move brings to the table. However, whether it suits specific organiz...
Read more