🐥 Small Data, Big Party 🎉. London, we’ve arrived.
Heading to @BigData_LDN? Then join us join us at Kindred for an evening of connection, conversation, and a few surprises only MotherDuck (and our friends at @dagster@AirbyteHQ, @SecodaHQ, Tasman, @keboola, LEIT DATA & @Xebia)…
Next Monday at @pydataberlin, I’ll be giving a hands-on workshop:
“More than DataFrames: Data Pipelines with the Swiss Army Knife DuckDB”
I’m also bringing some Duck swag for the bravest!
pydata.org/berlin2025
I bet if you use the Postgres scanner through DuckDB (via DuckDB MCP), you’ll get the same magic results, but faster.
It’s fine to start your analytics in Postgres, but let the elephant rest and move them to a proper OLAP database.
I bet if you use the Postgres scanner through DuckDB (via DuckDB MCP), you’ll get the same magic results, but faster.
It’s fine to start your analytics in Postgres, but let the elephant rest and move them to a proper OLAP database.
I often refactor vibecoded stuff into more readable, structured files.
But maybe that’s counterproductive — it’s easier for humans, but harder for LLMs?
All roads lead to Rome, but there are 3 ways to get your Postgres analytics queries from painfully slow to lightning fast ⚡
Watch the latest video of @mehd_io to understand 3 distinct paths to DuckDB integration, each with its own pros/cons👇
youtu.be/86V4wbFtuaY
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