Immortal DB

Transaction time support for SQL server

David Lomet, Roger Barga, Mohamed Mokbel, German Shegalov, Rui Wang, Yunyue Zhu

Research output: Contribution to journalConference article

37 Citations (Scopus)

Abstract

Immortal DB builds transaction time database support into the SQL Server engine, not in middleware. Transaction time databases retain and provide access to prior states of a database, An update "inserts" a new record while preserving the old version, The system supports as of queries returning records current at the specified time. It also supports snapshot isolation concurrency control. Versions are stamped with the times of their updating transactions. The timestamp order agrees with transaction serialization order. Lazy timestamping propagates timestamps to all updates of a transaction after commit, All versions are kept in an integrated storage structure, with historical versions initially stored with current data. Time-splits of pages permit large histories to be maintained, and enable time based indexing. We demonstrate Immortal DB with a moving objects application that tracks cars in the Seattle area.

Original languageEnglish
Pages (from-to)939-941
Number of pages3
JournalProceedings of the ACM SIGMOD International Conference on Management of Data
DOIs
Publication statusPublished - 1 Dec 2005
Externally publishedYes

Fingerprint

Servers
Concurrency control
Railroad tracks
Middleware
Railroad cars
Engines

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Immortal DB : Transaction time support for SQL server. / Lomet, David; Barga, Roger; Mokbel, Mohamed; Shegalov, German; Wang, Rui; Zhu, Yunyue.

In: Proceedings of the ACM SIGMOD International Conference on Management of Data, 01.12.2005, p. 939-941.

Research output: Contribution to journalConference article

Lomet, David ; Barga, Roger ; Mokbel, Mohamed ; Shegalov, German ; Wang, Rui ; Zhu, Yunyue. / Immortal DB : Transaction time support for SQL server. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. 2005 ; pp. 939-941.
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