As the speed gap between main memory and mod 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.