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Temporal Databases
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AbstractA temporal database stores time‐varying data and has the capabilities to manipulate it. Two commonly used time dimensions for maintaining temporal data are valid time and transaction time. Temporal databases are classified as valid time, transaction time, or bitmeporal databases. Temporality in databases involve subtle issues like comparing database states at different times, temporal grouping, different ways to represent the same temporal data, consistency of the timestamps of different attributes, temporal integrity constraints, and designing temporal databases. A temporal atom is a timestamp and value pair in which The timestamp is valid and/or transaction time and value are the time‐varying data. For representing and manipulating temporal data, data models handle temporal atoms differently. In relational data model, which is the focus of this entry, attribute or tuple time stamping may be used. Temporal algebra and temporal calculus languages are defined accordingly. Proposals for extending SQL2 for temporal data manipulation exist, and SQl3 supports user‐defined data types that can be used for defining and manipulating temporal data. This entry covers temporal query languages and the temporal issues mentioned above.
Title: Temporal Databases
Description:
AbstractA temporal database stores time‐varying data and has the capabilities to manipulate it.
Two commonly used time dimensions for maintaining temporal data are valid time and transaction time.
Temporal databases are classified as valid time, transaction time, or bitmeporal databases.
Temporality in databases involve subtle issues like comparing database states at different times, temporal grouping, different ways to represent the same temporal data, consistency of the timestamps of different attributes, temporal integrity constraints, and designing temporal databases.
A temporal atom is a timestamp and value pair in which The timestamp is valid and/or transaction time and value are the time‐varying data.
For representing and manipulating temporal data, data models handle temporal atoms differently.
In relational data model, which is the focus of this entry, attribute or tuple time stamping may be used.
Temporal algebra and temporal calculus languages are defined accordingly.
Proposals for extending SQL2 for temporal data manipulation exist, and SQl3 supports user‐defined data types that can be used for defining and manipulating temporal data.
This entry covers temporal query languages and the temporal issues mentioned above.
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