An Evaluation of B-tree Compression Techniques

B-trees are widely recognized as one of the most important index structures in database systems, providing efficient query processing capabilities. Over the past few decades, many techniques have been developed to enhance the efficiency of B-trees from various perspectives. Among them, B-tree compre...

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Veröffentlicht in:The VLDB journal Jg. 35; H. 1; S. 4
Hauptverfasser: Sun, Sikang, Gao, Chuqing, Ballijepalli, Shreya, Wang, Jianguo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer Nature B.V 01.01.2026
Schlagworte:
B trees
Concurrency control
Datasets
Queries
Query processing
Systems design
Trees
ISSN:1066-8888, 0949-877X
Online-Zugang:Volltext
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Zusammenfassung:B-trees are widely recognized as one of the most important index structures in database systems, providing efficient query processing capabilities. Over the past few decades, many techniques have been developed to enhance the efficiency of B-trees from various perspectives. Among them, B-tree compression is an important technique introduced as early as the 1970s to improve both space efficiency and query performance. Since then, several B-tree compression techniques have been developed. However, to our surprise, we have found that these B-tree compression techniques were never compared against each other in prior works. Consequently, many important questions remain unanswered, such as whether B-tree compression is truly effective or not. If it is effective, under what scenarios and which B-tree compression methods should be employed? In this paper, we conduct an experimental evaluation of seven widely used B-tree compression techniques using both synthetic and real datasets. Based on our evaluation, we present lessons and insights regarding the use of B-tree compression that can be leveraged to guide system design decisions in modern databases.
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ISSN:1066-8888
0949-877X
DOI:10.1007/s00778-025-00950-8