Accelerating Queries of MongoDB by an FPGA-based Storage Engine: Work-in-Progress

Abstract

In this paper, we propose a storage engine for MongoDB to accelerate the queries and reduce the memory usage. An FPGA-based query accelerator is deployed to speed up the queries while hot data is migrated from memory to SSD to reduce memory occupancy by our storage engine. Moreover, multiple query tasks of MongoDB are performed in parallel and query conditions are parameterized to support diversified queries. Based on TPC- H benchmark and Tencent data set, experimental results demonstrate that our storage engine can achieve higher query efficiency (saving up to 63.5 % time overhead) and lower memory occupancy (reducing up to 73.4 % memory usage) compared with traditional MongoDB.