Abstract: As the speed gap between main memory and modern processors continues to widen, the cache behavior becomes more important for main memory database systems (MMDBs). Indexing technique is a key component of MMDBs. Unfortunately, the predominant indexes --- B⁺-trees and T-trees --- have been shown to utilize cache poorly, which triggers the development of many cache-conscious indexes, such as CSB⁺-trees and pB⁺-trees. Most of these cache-conscious indexes are variants of conventional B⁺-trees, and have better cache performance than B⁺-trees. In this paper, we develop a novel J⁺-tree index, inspired by the Judy structure which is an associative array data structure, and propose a more cache-optimized index --- Prefetching J⁺-tree (pJ⁺-tree), which applies prefetching to J⁺-tree to accelerate range scan operations. The J⁺-tree stores all the keys in its leaf nodes and keeps the reference values of leaf nodes in a Judy structure, which makes J⁺-tree not only hold the advantages of Judy (such as fast single value search) but also outperform it in other aspects. For example, J⁺-trees can achieve better performance on range queries than Judy. The pJ⁺-tree index exploits prefetching techniques to further improve the cache behavior of J⁺-trees and yields a speedup of 2.0 on range scans. Compared with B⁺-trees, CSB⁺-trees, pB⁺-trees and T-trees, our extensive experimental study shows that pJ⁺-trees can provide better performance on both time (search, scan, update) and space aspects.