System and method for capture of change data from distributed data sources, for use with heterogeneous targets
A distributed data and data capture technology, applied in database update, special data processing application, structured data retrieval, etc., can solve the problem that the database or data replication system cannot fully expand the data, etc.
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[0027] As mentioned above, organizations may sometimes need to move data between different database environments, for example, to create backups of data, or to enable data sharing between different database applications. Data replication systems help address this need, for example by detecting and replicating changes to data in database tables as a result of row operations, instead of copying entire tables and the data within them. This method can be used to synchronize the data in the target database with the data in the source database. However, environments that support very large data sets, such as big data environments, pose challenges related to availability, scalability, and fault tolerance.
[0028] For example, a data replication system that operates to read a commit log or transaction log to extract changes in a data source faces the following challenges: the source system may have more than one copy of data on various nodes; the source system is partition tolerant ...
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