In database query processing, aggregation is an operator by which data with a common property is grouped and expressed in a summary form. Early aggregation is a popular method for improving the performance of the aggregation operator. In this paper, we study early aggregation algorithms in the context of query processing acceleration in database systems on FPGAs. The comparative study leads us to set-Associative caches with a low inter-reference recency set (LIRS) replacement policy. They show both great performance and modest implementation complexity compared to some of the most prominent early aggregation algorithms. We also present a novel application-specific architecture for implementing set-Associative caches. Benchmarks of our implementation show speedups of up to 3x for end-To-end aggregation compared to a state-of-The-Art FPGA-based query engine.