alterneesh

Location: India

Remote: Yes

Willing to relocate: In India, yes

Technologies: Python, Golang, SQL, c++, git, docker, k8s, MySQL, elasticsearch, redis, gin, flask, spark

Over the last two years, I've become borderline obsessed with everything happening in the data space, right from core database innovations (like duckdb), workflow and data orchestration tools (like prefect and airbyte), to niche products in data lineage and observability (like Atlan, great expectations). Therefore, to summarize, I'd like to work on building tools for/with big data :)

That being said, I've realised that there are interesting aspects at every abstraction in Computer Science! :) For example, Clojure is something I've been meaning to get into for a while and NLP is something I always like working on. So, feel free to reach out if you think I'd be a good fit!

Blog: https://aneesh.mataroa.blog/

Résumé/CV: https://drive.google.com/file/d/111XAKGnU9PApwmLtFmZdHDjMsNQ...

Email: makalaaneesh18 {at} gmail {dot} com

LinkedIn: https://www.linkedin.com/in/makalaaneesh/

Thanks! Didn't know this existed

Fair, fair. I do have a decent network locally. It's just that I'm interested in landing a fully remote role at some of these global distributed startups where I can't leverage my network.

Thanks, that's very useful. Have been trying to customize my applications. Will definitely continue to do so! :)

I just skimmed through the article tbh, but I saw 14 GB and what looked like a predicate pushdown optimization. I think DuckDB could handle that on my 16GB mac.

Regarding tab groups, there's two things that I've found that seems to have solved my requirements: - Workona (this is an extension for chrome) - Arc (https://thebrowser.company/)

Both essentially have the idea of "spaces" for web browsers.

Fair point about the "recentness". I guess it seemed recent to me since I learned about it only a few months back :)

Also, yes, 100%. Columnar storage fits well with vectorized execution! Thanks for sharing

I can't seem to understand why vectorization wouldn't help, say if you read after a sort. Irrespective of whether it fits in memory, or you perform some sort of an external sort, any operation that you want to perform on top of that sorted vector, be it an aggregation to reduce it, or an arithmetic operation with another column, you could still leverage vectorization and would end up using fewer CPU cycles, no?