Hey folks, forgive the potentially dumb question.<p>I've been using standard RDBMSs (mostly MySQL and PostgreSQL) for a little over 20 years, but I've never dabbled in Data Warehouses. I'm trying to understand the technical differences between the two.<p>The top answer on (my) google search for "differences between a database and a data warehouse" is that "a database is any collection of data organized for storage, accessibility, and retrieval. A data warehouse is a type of database the integrates copies of transaction data from disparate source systems and provisions them for analytical use."<p>That speaks more to the purpose of the Data Warehouse, and less to its underlying structure.<p>I've also come across articles that espouse the benefits of a Data Warehouse in terms of OLAP (versus OLTP). I understand the basic premise of this, but yeah I'm just trying to picture what it is about a Data Warehouse under the hood that makes it superior.<p>Can you kind folks please point me in the right direction? Technical depth welcome.<p>Thanks!
IME a warehouse is usually accommodating of structured and unstructured data, has decoupled storage and compute, and is optimized for analytics/big data (as opposed to app-tier databases which are normally optimized for throughput).<p>I think the buzzword is really centered around intent, not actual technical ability. You _could_ use Postgres as a data warehouse, given it supports JSON types, but you wouldn't be taking advantage of all the innovation that's gone into the warehousing space.
I don't think there's an "under the hood" to speak of. A Data Warehouse could be built out of RDBMSs or something else.<p>I think it's mostly a buzzword, but if I had to define it, I'd say that it's a data store which isn't directly involved in operating your product, rather, it's data that you gathered and stored outside of the product, to allow data geeks to run their analysis jobs without them needing to touch your production database.