2006/01/01 by Goetz Graefe, Graefe, Goetz
Computer Science · #Advanced Database Systems and Queries #B-tree #Data Management and Algorithms #Data Mining Algorithms and Applications #high update rates
paper · doi:10.4230/dagsemproc.05421.3
openalex publication_date 2006/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In some applications, data capture dominates query processing. For example, monitoring moving objects often requires more insertions and updates than queries. Data gathering using automated sensors often exhibits this imbalance. More generally, indexing streams apparently is considered an unsolved problem. For those applications, B-tree indexes are reasonable choices if some trade-off decisions are tilted towards optimization of updates rather than of queries. This paper surveys techniques that let B-trees sustain very high update rates, up to multiple orders of magnitude higher than tradi-tional B-trees, at the expense of query processing performance. Perhaps not surprisingly, some of these techniques are reminiscent of those employed during index creation, index rebuild, etc., while others are derived from other well known technologies such as differential files and log-structured file systems.