You would be... surprised.
The query engine in Microsoft SQL Server is absurdly advanced, and simply beats the pants off just about everything else for complex, general-case queries. There are other engines that are better tuned for special cases, but if you've got "stuff" that's within the capacity of a single box, it's really hard to beat MSSQL.
Let's expand on my example above: Clustered ColumnStore.[1]
It's basically PowerBI or Vertica embedded within the traditional MSSQL engine. This extension enables the ability to have a per-column (vertical) on-disk storage format instead of the traditional row-store format most databases have.
You can have it as a secondary acceleration index, or as a clustered (primary) index. In the latter case, it'll compress your raw table data. For my log files it was 33-to-1 compression (3% of the original file size).
Second, even if the data doesn't fit into memory, it'll utilise the columnar storage to simply ignore (skip) columns it doesn't need for the query. I was computing performance statistics, so it was just reading in some numbers instead of the text. A further 100-to-1 optimisation can be gained here.
It then parallelises this across all cores/hyperthreads, so I get 100% utilisation on 16 cores.
All of this I/O is fully asynchronous with a huge queue depth. Expect to see 200K IOPS on a laptop, easily.
Once in memory, it uses Intel AVX SIMD instructions to chew through the data 8 rows per clock tick per core. With 8 cores going at once, this is 64 rows per clock, or up to 234 billion rows processed per second.
What's neat about it is that it's fully general: Columnstore can be mixed -- in a single query -- with in-memory tables, on-disk tables, traditional row-store, and external tables streamed in over the network. The engine will just... "figure this out". It'll build indexes on the fly if it has to, ideally in memory, but failing that... it'll stream disk-to-disk as required. I've seen "sort spills" reach 600K IOPS on my laptop.
If I have to scan through years of logs and be able to join it against additional tables for "enriching" it, then it's hard to beat. Sure, there's a scale where the are dedicated log analytics databases, but they have their quirks, limitations, and costs.
I take your incredulity that others can fully utilise their computers as a sign that general knowledge of just what is possible is poor. People have pointed out that some simple shell scripts can outperform Hadoop clusters up to a surprising scale. Similarly, knowledge of the capabilities of traditional database engines like MSSQL is oddly lacking, even amongst developers. Not to mention more esoteric ways of making your computer do your bidding, such as Mathematica, Julia, GPU codes, or whatever.
Your computer is a power tool for your squishy, manual-labour meat brain! A lever for the mind. Learn to utilise it better and you'll be better at thinking.
[1] https://docs.microsoft.com/en-us/sql/relational-databases/in...