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Data synchronization is the process of establishing consistency between source and target data stores, and the continuous harmonization of the data over time. It is fundamental to a wide variety of applications, including file synchronization and mobile device synchronization.
In UI data binding, data and information objects of the same language, but different logic function are bound together (e.g., Java UI elements to Java objects). [1] In a data binding process, each data change is reflected automatically by the elements that are bound to the data.
Any changes made by a writer will not be seen by other users of the database until the changes have been completed (or, in database terms: until the transaction has been committed.) When an MVCC database needs to update a piece of data, it will not overwrite the original data item with new data, but instead creates a newer version of the data item.
Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. [1] There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories).
Atomicity between two parallel transactions with a conflict In concurrent programming, synchronization is required when parallel threads attempt to access a shared resource. Low-level thread synchronization constructs such as locks are pessimistic and prohibit threads that are outside a critical section from running the code protected by the ...
Synchronization ensures that memory writes by a thread before or during a synchronized block are made visible in a predictable manner to other threads which synchronize on the same monitor. After we exit a synchronized block, we release the monitor, which has the effect of flushing the cache to main memory, so that writes made by this thread ...
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SymmetricDS is open source software for database and file synchronization with Multi-master replication, filtered synchronization, and transformation capabilities. [2] It is designed to scale for a large number of nodes, work across low-bandwidth connections, and withstand periods of network outage. [3]