adam_oxla

5 ms·

1.
by adam_oxla 3y ago
Amazing overview. Right now I work on a completely new OLAP database: vectorized query execution is must have nowadays if you want to have competitive performance. What's interesting is that vectorized query engines benefits a lot from
2.
by adam_oxla 3y ago
I was working in Google in years 2013-2016. It was amazing experience at that time. In no other place I have learned so much on how to run large organizations efficiently: before I was working in several companies having tens employees and
3.
by adam_oxla 3y ago
While I do agree that for most of companies those large SaaS solutions are overkill I do not think that DuckDB or similar is sufficient. Nowadays more of the companies really need to process large datasets. I meet regularly companies that u
4.
by adam_oxla 3y ago
It is surprising how popular is using O(N^2) algorithms that are simple in implementation even in extremely popular libraries. E. g. ICU search method: https://github.com/unicode-org/icu/blob/a7a2fdbcf257fa22c
5.
by adam_oxla 3y ago
Great article. I was recently wondering why are vector databases useful at all. There are cases (LLMs) where they are useful. But apart from that, most of the cases I have encountered, requires indexing on different data types than vector.
6.
by adam_oxla 3y ago
Amazing article. I have not seen such a comprehensive guide yet. Although when I have seen the title I was expecting it would be focused more on CPU inner workings: superscalar pipelines, frontend, backend, instruction fusing, memory banks,