I am recently working on a time series data project to store some sensor data.To achieve maximum insertion/write throughput i used capped collection(As per the mongodb documentation capped collection will increase the read/write performance). when i test the collection for insertion/write of some thousand documents/records using python driver with capped collection without index against the normal collection, i couldn't see much difference in improvement in write performance of capped collection over normal collection. example is like i inserted 40K records on single thread using pymongo driver. capped collection took around 25.4 seconds and normal collection took 25.7 seconds.
Could anyone please explain me when can we achieve maximum insertion/write throughput of capped collection? Is this is the right choice for time series data collections?
Data stored into capped collections are rotated upon exceeding fixed size of capped collection . Capped collections don't require any indexes as they preserve the insertion order and also data is retrieved in natural order same as order in which the database refers to documents on disk.Hence it offers high performance in insertion and data retrieval process.
For more detailed description related to Capped collections please refer the documentation as mentioned in URL
https://docs.mongodb.com/manual/core/capped-collections/