Incremental Data Migration and Replication in Software

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Incremental Data Migration and Replication
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Incremental data migration is the process of synchronizing the source and the destination systems by moving only the changed data (instead of the complete set) since the last synchronization process When the incremental data migration happens in real time, it is called real-time replication The key requirement of the incremental data migration is the ability to capture changed data from the source system using an appropriate change
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data capture (CDC) strategy Some of the CDC methods that can be used for capturing changes are
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Data model based CDC In order for the source database to support a data model based CDC, the tables on the source database should be able to capture the timestamp of all the DML activity as it occurs on the source system This is usually accomplished by using a column that stores a row modified (or inserted) timestamp for every row The incremental extracts can use this timestamp to pull out only the changed rows since the last synchronization process However, deletes will have to be captured in a separate log table using mechanisms such as delete triggers Trigger-based CDC Triggers can be defined on the source tables to execute when insert/update/delete activity occurs allowing it to take further actions The triggers can be programmed to capture changes in a separate log table, or even propagate the changes directly to the destination database using queuing-based mechanisms Log-based CDC Almost all databases have some sort of journalizing capability Journalizing is the process of capturing database transactions (or modifications) in a log file, which is stored in a format that is proprietary to the database vendor Most database vendors provide an interface to these log files using an Application Programming Interface (API) By mining the log files using the API, it is possible to re-create the SQL as it occurred on the source database and then execute it against the destination database, at the same time preserving the transactional integrity of the DML Real-time replication tools are based on the ability to mine database transaction logs in real time Based on the CDC strategy chosen, the methods that can be used for performing the incremental loads can be determined Broadly speaking, the incremental load methods can be categorized into near real-time and real time
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Near real-time incremental loads When the CDC is performed by using the data model approach, then the incremental loads can, at best, be done in near real-time Each run of the incremental load process will synchronize a batch of transactions that will be queued
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up to be processed How near to real time the loads are is determined by the time it takes the incremental load to synchronize a batch without causing a measurable impact on the source system The methods available for performing near real-time incremental loads are using custom extract and load scripts and ETL tools like Oracle Data Integrator The custom scripts and ETL mappings created for performing initial loads can also be used to perform incremental loads by modifying the SQL to extract only the changed rows since the last run instead of the complete data
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Real-time incremental loads Using the log-based CDC approach, changes can be replicated as they occur on the source system in real time to the destination system The Oracle tools that support real-time replication using the log-based CDC approach are Oracle GoldenGate and Oracle Data Integrator Both tools can perform replication from heterogeneous sources to the Oracle database In the next section, we will discuss the capabilities and guidelines that will help you choose the right tool Using automated tools to perform real-time incremental loads is the most preferred method for performing real-time synchronization of data between the current source and the Database Machine This method does not need the data model to support change data capture, as the tools are capable of capturing changes using built-in mechanisms Also, the work involved in the setup and configuration of the tools is much less when compared to the custom scripts method
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