Planar point location using persistent search trees
Communications of the ACM
Expected behaviour of B+-trees under random insertions
Acta Informatica
The log-structured merge-tree (LSM-tree)
Acta Informatica
Constructing Optimal Search Trees in Optimal Time
IEEE Transactions on Computers
A Cost Model for the Internal Organization of B+-Tree Nodes
ACM Transactions on Programming Languages and Systems (TOPLAS)
Incremental Organization for Data Recording and Warehousing
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Cache Conscious Indexing for Decision-Support in Main Memory
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Database Architecture Optimized for the New Bottleneck: Memory Access
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
A Novel Index Supporting High Volume Data Warehouse Insertion
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Real-Time Data Access Control on B-Tree Index Structures
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Fat-Btree: An Update-Conscious Parallel Directory Structure
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
B-tries for disk-based string management
The VLDB Journal — The International Journal on Very Large Data Bases
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Modern ad-hoc data mining queries often run on databases over a terabyte in size. At this scale, large data pages are required to obtain sufficient disk performance. Unfortunately, these large data pages greatly increase update costs, especially for packed structures such as the B+ tree. In a frequently updated warehouse, users are often forced to decide between query performance and update performance in order to meet maintenance time windows. Solutions that provide both are welcome.In this paper, we analyze and measure the memory related costs of B+ Tree updates with large data pages. We introduce the RB+ (Red-Black+) tree as a practical replacement for the B+ tree. The RB+ tree uses persistent red-black binary trees instead of sorted records for leaf pages. This organization improves memory performance up to 3,000% for updates and provides query performance comparable to a B+ tree, making it practical for large, frequently updated warehouses.