It really depends on what type of querying you're doing. If the data is wide as you say, but you end up performing a large number of aggregate queries on colum

It really depends on what type of querying you're doing. If the data is wide as you say, but you end up performing a large number of aggregate queries on columns, like SUMming a bunch of values, then it might be worth looking at a columar store which structures your data on disk by column rather than by row. https://en.wikipedia.org/wiki/Column-oriented_DBMS https://en.wikipedia.org/wiki/Column-oriented_DBMS examples include AWS Redshift or even just Postgres with some bells and whistles that end up doing the same thing. Again though, I go back to my first point and try and get a good characterization of how the data is typically access, a million rows per year isn't much and you might just get a lot further with some indexing strategies in your regular RDBMS.