Remote work was a mistake. After two years of being fully remote, we're now going back to in-office.
This is a hard task because we need to relocate every team member.
Check out our new headquarter and why we are getting back in person.
A thread 🧵
@DuckDB now supports upserts through the "on conflict" clause!
For now, you just need to install from the latest master branch, but this will be in the next release!
https://t.co/UsxZgHESVg
If you're a data nerd, you won't want to miss this article on the shift from the modern data stack to the modern data graph. By @stkbailey.
https://t.co/ye5dOenO01
PyCon PH is back! 🎉
It's been almost 4 years since we hosted PyCon APAC 2019 and went on a strategic pause. Finally, PyCon Philippines is back with the theme "ugnayan", celebrating the connections we formed and continue to build as a community. Stay tuned and see you next year!
Friend or foe? Let’s break down the ways that AI can ⚡supercharge⚡ our decisions to improve our daily lives and how we do business. Follow our blog post series, We’re Better with AI, for more content on becoming an AI-driven organization. Full post at https://t.co/wht10Q147e.
Without DuckDB our current lead project would not exist. In a closed environment w/o access to internet (cloud) and only python available we need to analyze ~1B transactions + 128M rows dataset (+ several ~5M rows ones).
Once the db is set up, even complex queries take ~15 secs
@hfmuehleisen I watched your CWI talk (https://t.co/tMGVqEc6fL). For the Spark vs Duck DB tests that you did, how did you get data into the duckdb node? I know Spark can do it via its multiple data connectors. Would like to know what a good practice for duckdb would be
Today I talked to a startup doing so well that they had no current problems that needed solving. Profitable, growing ~20x a year (not a typo), only 9 employees. This is so rare that I didn't know what to do. We ended up talking about problems they might have in the future.
Hi @duckdb! This is driving me nuts: what is the difference between using a persistent database (e.g. in python: duckdb.connect(database="database.duckdb")) vs saving the contents of a DB using EXPORT and then using IMPORT in subsequent sessions?
The power of @DuckDB and @ApacheArrow:
"We can select 304,851 interesting rows from all 1,547,741,381 in the 10 year dataset in < 3 seconds on a laptop!"
Great demo!