i think good example too is clickhouse analytics db, their development is all on github, fun to read issues and release notes every once in a while
Ask HN: What does database (internals) development look like?
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Re: Ask HN: What does database (internals) development look like?
#12Start by watching Michael Stonebraker's Turing Award lecture, he will give you the lowdown and inspiration: https://youtu.be/BbGeKi6T6QI Start with relational, understand why it is the reference architecture, and from there the tradeoffs involved and what other architectures bring to the table (columnar, streaming, object, in-memory, array, distributed, blockchain, nosql, etc) To really understand why you should star…
wow, these resources are pretty great.
I would like to add that CMU’s Database course by Andy Pavlo is quite nice and they go in really in-depth explaining the internals. Really fun lectures!
Re: Ask HN: What does database (internals) development look like?
#13Start by watching Michael Stonebraker's Turing Award lecture, he will give you the lowdown and inspiration: https://youtu.be/BbGeKi6T6QI Start with relational, understand why it is the reference architecture, and from there the tradeoffs involved and what other architectures bring to the table (columnar, streaming, object, in-memory, array, distributed, blockchain, nosql, etc) To really understand why you should star…
I forgot to add these great notes from Stonebraker's MIT database course:
http://marcua.net/notes/6.830/
Re: Ask HN: What does database (internals) development look like?
#14i think good example too is clickhouse analytics db, their development is all on github, fun to read issues and release notes every once in a while
The C++ code is a model as well. Alexey Milovidov keeps things very clean.
Re: Ask HN: What does database (internals) development look like?
#15Data needs vary from company to company or application. Several things that come to mind are speed, accuracy, scalability, potability, and specific use cases (i.e. medical, GIS...).
As data needs will vary so does skills and knowledge. Best to figure out what sort of field of data that interests you and learn towards the environments that are used in it.