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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 cacheoptimized 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.