![[Paper Reading] Adaptive Radix Tree - ARTful Indexing for Main-Memory Databases event](/_next/image/?url=https%3A%2F%2Ffirebasestorage.googleapis.com%2Fv0%2Fb%2Ftech-career-growth.appspot.com%2Fo%2Fevent_images%252F1731449363-image.jpg%3Falt%3Dmedia%26token%3Dc9f48a7e-ab4c-43da-b3f4-fbe51475d053&w=3840&q=75)
https://db.in.tum.de/\~leis/papers/ART.pdf
This paper reading session, we will deep dive into a in-memory optimized index structure, that leverages modern CPU caches to make IOPS faster, also allowing range queries.
Abstract—Main memory capacities have grown up to a point where most databases fit into RAM. For main-memory database systems, index structure performance is a critical bottleneck. Traditional in-memory data structures like balanced binary search trees are not efficient on modern hardware, because they do not optimally utilize on-CPU caches. Hash tables, also often used for main-memory indexes, are fast but only support point queries.