Unfortunately there is no "out-of-the-box" solution for what you are trying to do. It depends on the actual database (or storage solution) that you actually em

Unfortunately there is no "out-of-the-box" solution for what you are trying to do. It depends on the actual database (or storage solution) that you actually employ; for example: * in case of Postgres there is streaming replication; but I think by default (and perhaps there isn't a way to disable that) it also "streams" `DELETE` operations; so you still have to do things manually; * in case of CouchDB (a document store) you could use replication, and then on the "on-premise server" (i.e. in company A) delete the old data and filter this operation in the replication; However, in the end I bet you'll end-up implementing a custom replication procedure. Which is not impossible, but not quite easy when you take into account network reliability. ---- A "quick and dirty" solution would be this: * dump data (either in SQL, JSON, TSV or whatever fits your use-case) in batches, of say 1 day or 1 week per batch; compress that with `zstd` or `lzip`; (depending on your data it should compress quite nicely to at least 75%;) * upload that to S3 for archival or staging area; * if you need on-line access to the data, import it in your database on AWS side;