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A temporal database stores data relating to time instances. It offers temporal data types and stores information relating to past, present and future time. Temporal databases can be uni-temporal, bi-temporal or tri-temporal. More specifically the temporal aspects usually include valid time, transaction time and/or decision time.
In a database table, the transaction time is often represented as an interval allowing the system to "remove" entries by using two table-columns start_tt and end_tt. The time interval is closed [at its lower bound and open) at its upper bound. [8] When the ending transaction time is unknown, it may be considered as until_changed.
Notably both of Oracle's implementations depend on the database's rollback segment and so only allow temporal queries against recent changes which are still being retained for backup. Microsoft SQL Server (version 2016) implements temporal tables with SYSTEM_VERSIONING. [13] MariaDB 10.3 implements system-versioned tables. [14]
Time series datasets can also have fewer relationships between data entries in different tables and don't require indefinite storage of entries. [6] The unique properties of time series datasets mean that time series databases can provide significant improvements in storage space and performance over general purpose databases. [ 6 ]
In temporal databases, valid-time is the time period when an event happened or something was true in the real world, or more formally when a fact was valid in the modeled reality. The valid-time period is an interval based on event times, which are referred to as event datetime in data vault .
Transact-SQL is central to using Microsoft SQL Server. All applications that communicate with an instance of SQL Server do so by sending Transact-SQL statements to the server, regardless of the user interface of the application. Stored procedures in SQL Server are executable server-side routines. The advantage of stored procedures is the ...
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Bitemporal modeling is a specific case of temporal database information modeling technique designed to handle historical data along two different timelines. [1] This makes it possible to rewind the information to "as it actually was" in combination with "as it was recorded" at some point in time.