The "yet another" moniker is used throughout technology. YAAF, YARN, YAML, and more ways that people talk about yet another way to solve some problem or build a platform. That's one of the amazing things about technology is that we, as a group, are not satisfied with the way things are done. Someone is constantly looking to find a better solution and advance our technology choices in a new direction.

In the database world, we've seen changes as well. Relational databases were the obvious, or perhaps just dominant, choice for most of my career. At some point I saw object databases, XML databases, then streaming databases, none of which gained much popularity. The last few years have seen document databases, graph databases, key value databases, and more. We categorize databases as row-store or column-stores now. There are probably other types I'm forgetting.

There are also categorizations of OLTP, OLAP, operational, ODS, data warehouses (DW), etc. that people use. I ran across a piece called "Why you need another database", whose opening line is "Do you really need yet another database?" The answer is, sure, you need an analytical database, but I think the piece is a bit behind the times. Lots of people have built an analytic database in the form or a relational DW, an SSAS cube, or perhaps some other type of NoSQL store (Hadoop is popular) that allows analysis of data away from an operational, every day OLTP system.

I would guess many of you have some separate reporting copy of data that allows analysis separately from your online system. This could be a copy of your production database, a data warehouse receiving regular loads, a read-only AG replica, or something else. Some of you might perform analysis in your primary OLTP system, with enough spare capacity to handle the reporting load.

There are multiple ways in which you may decide to implement an analytical database, but I do agree that most businesses ought to have some way of analyzing the data they collect. The questions in the piece (structure, size, analytics), are good ones, and no matter what your platform, architecture, or technology, make sure that you build something that meets the needs of your organization as a whole, not just the technologists that prefer one decision over another.