Which database management system type to choose for price tracking? I'm writing a price tracking application.  

Every day I need to store price information about ~15M products. (So it's about 15M * 365  = 5.5B records per year).

One product has many prices over history. My main table (if I opt for a SQL DBMS) should include the following attributes:


product_id (8bytes int)
price (4bytes int) can be NULL
date (only date without time since daily update)
currency (3byte string)


E.g. (9223372036854, 85.41, 14-01-2019, "USD")

I don't want to mark the latest price as 'active' or something, so I'm interested only in price history itself. The database should have high IO throughput (~1000 simultaneous reads). 

Queries I'm planning to run:


Get all price for the specific product_id for the specific time range 
Basic math operations like min, max, avg


So, I am curious:


Should I stick to a SQL DBMS (Postgres) or use some NoSQL product (e.g. Amazon Redshift)
Which DBMS can you recommend?
I would suggest building a test system using whatever DBMS you're most familiar with.  As speed is a mission-critical requirement, I would put the data on an NVMe SSD, and load it up with as much fake data as you can create, then put that through a rigorous set of tests.

Back-of-the-envelope calculations suggest you'll need around 100 GB of space for a years-worth of data, so a 1 TB NVMe SSD should suffice.  Of course, if data redundancy is a concern, you may want two, with data being mirrored between them.

PostgreSQL should have no difficulty handling your data.