Exploiting parallelism is the name of the game for executing analytical queries with low latency in in-memory database engines. Most prominently, modern general-purpose CPUs, which continue to dominate the area of computing units, offer high-computational power through two data-oriented parallel paradigms: MIMD and SIMD. Unfortunately, as both parallel paradigms exhibit different programming models and memory access patterns, exploiting both in a combined fashion is challenging. However, recent hardware advances for SIMD on CPUs have relaxed the restrictions on SIMD-friendly memory access patterns. The availability and performance of alternative access patterns has improved significantly compared to the state-of-the-art of a pure linear access pattern. As we will demonstrate in this paper, these advancements pave the way for a unified parallelization approach that harnesses both MIMD and SIMD in a combined fashion, offering a novel and promising way for an efficient analytical query processing.