![]() ![]() We looked at the performance (in)difference in match vs. This was a brief explainer on the differences between the find operation and match stage. It abstract away the nuances and provides a clean & concise way of getting the right insights out of your data. Finally, iterate over the results of step #2 again to collect the final results with rating greater than 7.Īs you would have observed, aggregation pipeline is very useful in complex scenarios like this.Iterate through all the entries and store the lowest movie rating for every given release year,.Perform a find operation to fetch ALL the data,.How can we implement the same with a find operation? Let's brainstorm: Here's how a document of our sample shipwrecks collection looks like: We will execute match and find on the same collection (and thus, same indexes). We have a sample dataset hosted on the free tier of Atlas Cloud for the purpose of this comparison. Let's try to perform both of these operations on a same dataset to see for ourselves. There are a lot discussion in the community regarding the speed differences of match stage vs a simple find operation for fetching data. ![]() It can be used independently, outside of an aggregation pipeline and it has no such restrictions as the $match stage has. Only the matched documents proceed to the next stage of the aggregation pipeline.įind operation on the other hand, is completely opposite. ![]()
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