I would pick Postgres. Tables are the best format for data storage, SQL is the best language for exploring them, and Postgres is the best SQL database. With its

I would pick Postgres. Tables are the best format for data storage, SQL is the best language for exploring them, and Postgres is the best SQL database. With its support of myriad contraints, aggregate functions, and data types, including JSON, you should be able to build whatever view into the data that the different people want, with either database views or functions. You might have to copy data into different databases (or just different schemas) for different teams, but maybe not. Datasets of a certain size might make Postgres fall over, but I don't think you're anywhere near that. That doesn't mean I would always stuff all my data into Postgres raw. I don't put Word documents or images in Postgres. I leave my Apache log files as Apache log files. If I want to analyze them, I usually use Bash (sed, cut, sort, etc.). But if I want to get really fancy I will import them into Postgres to run SQL queries on them, but usually just a certain segment of them (3 months, a year, etc.), only certain rows (grep first) and only certain columns (awk first). If your data infrastructure is staid and boring, I think it's a good sign that you're doing it right.