ACM Transactions on Database Systems (TODS)
An asymptotically optimal multiversion B-tree
The VLDB Journal — The International Journal on Very Large Data Bases
SNAP: Efficient Snapshots for Back-in-Time Execution
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Immortal DB: transaction time support for SQL server
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Thresher: an efficient storage manager for copy-on-write snapshots
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
Skippy: a new snapshot indexing method for time travel in the storage manager
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Adapting microsoft SQL server for cloud computing
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Windows Azure Storage: a highly available cloud storage service with strong consistency
SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
ProRea: live database migration for multi-tenant RDBMS with snapshot isolation
Proceedings of the 16th International Conference on Extending Database Technology
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Database backups have traditionally been used as the primary mechanism to recover from hardware and user errors. High availability solutions maintain redundant copies of data that can be used to recover from most failures except user or application errors. Database backups are neither space nor time efficient for recovering from user errors which typically occur in the recent past and affect a small portion of the database. Moreover periodic full backups impact user workload and increase storage costs. In this paper we present a scheme that can be used for both user and application error recovery starting from the current state and rewinding the database back in time using the transaction log. While we provide a consistent view of the entire database as of a point in time in the past, the actual prior versions are produced only for data that is accessed. We make the as of data accessible to arbitrary point in time queries by integrating with the database snapshot feature in Microsoft SQL Server.