hello, I hope this is the right channel to ask questions. We have an application that aggregates vulnerabilities from multiple scanners and provides visibility into that dataset. The data is being stored as collections in mongodb (odd choice but wasn't in my control). The data, however, is relational. for example, there are vulns that are related to assets which are related "asset groups" etc. Now I am trying to add some statistics like "lifecycle of an asset", "average time to resolution", "list of assets for which the vulns aren't closed within a certain number of hours" etc, and clearly mongodb is not built for this workload. I am looking at pinot (and other olap solutions) to see if we can optimize our queries without migrating our db entirely at the cost of data duplication between mongodb and perhaps pinot. It would be a great help if you guys can point me the right direction. If anyone has ever been in a similar situations, then insights and experience from that would be really appreciated. Thank you.

Yes this is a good use case for Pinot. We will be happy to help with your use case