We currently use a lot of MongoDB aggregation pipeline to do some data processing. However quite often we hit some performance issues. I am thinking of reading data from MongoDB into the Pandas dataframe and process the data with Pandas dataframe aggregation. Does anyone have any experience comparing the two approaches? Also, does the MongoDB aggregation pipeline utilizes some kind of parallelism inside?
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