CDC (Change Data Capture)
It can be called the process of defining and capturing changes made in the database. It is also referred to as a design pattern to identify and track changes in this type of database.
Unlike traditional methods, it finds and updates changes in data instantaneously instead of batch processing. Differences between CDC and batch processing can be as follows.
CDC
– Updates the target database instantly.
– Continuously monitors changes in the source database.
– Uses the process flow to provide instant changes.
Batch Processing
– Data are not synchronized immediately.
– Allocating resources to maintain synchronization slows production.
– Replication process takes place during batch Windows.
First state and last state information can be logged from modern databases. The current sysdate is printed in a field in the form of Update date. Triggers from the source database can be used to capture data with CDC changes.
CDC can be used in two ways. It can be divided into asynchronous and asynchronous.
Synchronous Change Data Capture
Represents the SYNC SOURCE source database. Triggers run after performing DML operations on source tables populate the SYNC_SOURCE change resource.
Asynchronous HotLog Change Data Capture
HOTLOG_SOURCE represents online log files in the source database. It cannot be changed or deleted.
We can use the table below to query on source db.
SELECT * FROM ALL_CHANGE_SOURCES.
Asynchronous CDC has different methods. In summary, Oracle offers us as follows. The method can be used according to the need.
Factors Influencing Choice of Change Data Capture Mode
| Mode | Location of, Hardware, and Software on Staging Database | Capture Mechanism | Source Database
Performance Impact |
| Synchronous | Location must be the same as the source database and
therefore hardware, operating system, and Oracle Database release are the same as source system. |
Change data is automatically committed as part of the same transaction it reflects. | Adds overhead to source
database transactions to perform change data capture. |
| Asynchronous HotLog | Location must be the same as the source database and therefore hardware, operating system, and Oracle Database release are the same as source system. | Change data is captured from the current online redo log file. Change sets are populated automatically as new transactions are committed. | Minimal impact on source
database transactions to perform supplemental logging. Additional source database overhead to perform change data capture. |
| Asynchronous Distributed HotLog | Location is remote from the
source database. Hardware, operating system, and Oracle database release can be different from the source system. |
Change data is captured from the current online redo log file. The change set is populated automatically as new committed transactions arrive on the staging database. | Minimal impact on source
database transactions to perform supplemental logging.
Some overhead on the source database is incurred when mining the online redo log files. |
| Asynchronous AutoLog
Online |
Location is remote from the
source database. Hardware, operating system, and Oracle database release are the same as source system. |
Change data is captured from the standby redo log files. The change set is populated automatically as new committed transactions arrive on the staging database. | Minimal impact on source
database transactions to perform supplemental logging.
Minimal source database overhead for redo transport services. |
| Asynchronous AutoLog
Archive |
Location is remote from the
source database. Hardware, operating system, and Oracle database release are the same as source system. |
Change data is captured from archived redo log files. Change sets are populated automatically as archived redo log files arrive on the staging database. | Minimal impact on source
database transactions to perform supplemental logging. Minimal source database overhead for redo transport services |
It will be practical in the following articles…
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