The key objective of database systems is to efficiently manage an always increasing amount of data. Thereby, a high query throughput and a low query latency are core requirements. To satisfy these requirements, database engines are highly adapted to the given hardware by using all features of modern processors. Apart from this software optimization, even tailor-made processing circuits running on FGPAs are built to run mostly stateless query plans with a high throughput. A similar approach, which was already investigated three decades ago, is to build customized hardware like a database processor. Tailor-made hardware allows to achieve performance numbers that cannot be reached with software running on general-purpose CPUs, while at the same time, addressing the dark silicon problem. The main disadvantage of custom hardware is the high development cost that comes with designing and verifying a new processor, as well as building respective drivers and the software stack. However, there is actually no need to build a fully-fledged processor from scratch. In this paper, we present our conducted as well as our ongoing research efforts in the direction of customizing hardware for databases. In detail, we illustrate the potential of instruction set extensions of processors as well as of optimizing memory access by offloading logic to the main memory controller.