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Journal of Algorithms
Performance evaluation of a temporal database management system
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
Computer
Two algorithms for maintaining order in a list
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Making data structures persistent
Journal of Computer and System Sciences - 18th Annual ACM Symposium on Theory of Computing (STOC), May 28-30, 1986
Access methods for multiversion data
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Event-join optimization in temporal relational databases
VLDB '89 Proceedings of the 15th international conference on Very large data bases
The time index—an access structure for temporal data
Proceedings of the sixteenth international conference on Very large databases
Toward a unified framework for version modeling in engineering databases
ACM Computing Surveys (CSUR)
The performance of a multiversion access method
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Overlapping B+trees for temporal data
JCIT Proceedings of the fifth Jerusalem conference on Information technology
Efficient algorithms for managing the history of evolving databases
ICDT '90 Proceedings of the third international conference on database theory on Database theory
Segment indexes: dynamic indexing techniques for multi-dimensional interval data
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
The snapshot index: an I/O-optimal access method for timeslice queries
Information Systems
Designing DBMS support for the temporal dimension
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Incremental Implementation Model for Relational Databases with Transaction Time
IEEE Transactions on Knowledge and Data Engineering
Efficient Management of Time-Evolving Databases
IEEE Transactions on Knowledge and Data Engineering
Efficient Indexing Methods for Temporal Relations
IEEE Transactions on Knowledge and Data Engineering
Indexing Techniques for Historical Databases
Proceedings of the Fifth International Conference on Data Engineering
Proceedings of the Eighth International Conference on Data Engineering
On Optimal Multiversion Access Structures
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
Comparison of access methods for time-evolving data
ACM Computing Surveys (CSUR)
Designing Access Methods for Bitemporal Databases
IEEE Transactions on Knowledge and Data Engineering
Hashing Methods for Temporal Data
IEEE Transactions on Knowledge and Data Engineering
The BT-tree: A Branched and Temporal Access Method
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Supporting complex queries on multiversion XML documents
ACM Transactions on Internet Technology (TOIT)
Minuet: a scalable distributed multiversion B-tree
Proceedings of the VLDB Endowment
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Traditional approaches to addressing historical queries assume a single line of time evolution; that is, a system (database, relation) evolves over time through a sequence of transactions. Each transaction always applies to the unique, current state of the system, resulting in a new current state. There are, however, complex applications where the system's state evolves into multiple lines of evolution. In general, this creates a tree (hierarchy) of evolution lines, where each tree node represents the time evolution of a particular subsystem. Multiple lines create novel historical queries, such as vertical or horizontal historical queries. The key characteristic of these problems is that portions of the history are shared; answering historical queries should not necessitate duplication of shared histories as this could increase the storage requirements dramatically. Both the vertical and horizontal historical queries have two parts: a "search" part, where the time of interest is located together with the appropriate subsystem, and a reconstruction part, where the subsystem's state is reconstructed for that time. This article focuses on the search part; several reconstruction methods, designed for single evolution lines can be applied once the appropriate time of interest is located. For both the vertical and the horizontal historical queries, we present algorithms that work without duplicating shared histories. Combinations of the vertical and horizontal queries are possible, and enable searching in both dimensions of the tree of evolutions.