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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.
A special case of replication is synchronization, where there are only two replicas. For example, personal digital assistants (PDAs) allow users to edit data either on the PDA or a computer, and then to merge these two datasets together. Note, however, that replication is a broader problem than synchronization, since there may be more than two ...
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).
Each standby database applies (replays) the arrived redo, resulting in synchronization with the primary database. [ 5 ] If a database crashes, the recovery process has to apply all transactions, both uncommitted as well as committed, to the data-files on disk, using the information in the redo log files.
The PACELC theorem, introduced in 2010, [8] builds on CAP by stating that even in the absence of partitioning, there is another trade-off between latency and consistency. PACELC means, if partition (P) happens, the trade-off is between availability (A) and consistency (C); Else (E), the trade-off is between latency (L) and consistency (C).
SymmetricDS is database independent, data synchronization software. It uses web and database technologies to replicate tables between relational databases in near real time. The software was designed to scale for a large number of databases, work across low-bandwidth connections, and withstand periods of network outage.
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In multithreaded computing, the ABA problem occurs during synchronization, when a location is read twice, has the same value for both reads, and the read value being the same twice is used to conclude that nothing has happened in the interim; however, another thread can execute between the two reads and change the value, do other work, then change the value back, thus fooling the first thread ...