In this paper, we present a novel co-designed architecture for high throughput database query processing. It consists of a highly configurable FPGA-based filter chain with arithmetic operation support and an alignment unit. This feeds the filtered data directly and in a cache-optimized way to embedded processors which are responsible for joining tables and post processing. High throughput interfaces and parallelism of FPGA implementations are thus combined in order to provide reduced and cache-aligned data for optimized processor access. As a key component, we introduce a new highly configurable bloom filter cascade to relieve a processor of time-consuming hash-value computation and to significantly reduce the data for hash joins. It is shown that this unique approach may reduce the amount of data to be processed by the processors in typical data-warehouse applications by several orders of magnitude. The proposed co-design has been implemented on the embedded low-energy system-on-chip (SoC) platform Xilinx Zynq. Performance results for standard benchmarks show an up to 10 x higher throughput compared to a full featured x86-based processor at only a fraction of energy consumption.