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We're excited to share the 1.0 release of pg_duckdb, an open-source PostgreSQL extension that brings DuckDB's vectorized analytical engine directly inside PostgreSQL. You can think of it as adding a turbo engine to your PostgreSQL database–ready to run efficient, ad hoc queries while PostgreSQL continues doing what it does best: transactional workloads for your production app. Pg_duckdb embeds a D
Today, we’re releasing Instant SQL, a new way to write SQL that updates your result set as you type to expedite query building and debugging – all with zero-latency, no run button required. Instant SQL is now available in MotherDuck and the DuckDB Local UI. We built Instant SQL for a simple reason: writing SQL is still too tedious and slow. Not because of the language itself, but because the way w
The first cloud data warehouse to separate storage and compute was BigQuery, and was outlined in the Dremel paper in 2008. Yes, Jordan is a little bitter about this because Snowflake claimed to have invented it several years later. Of course, as one does, when Jordan mentioned this to some database guru, he was immediately corrected and told that IBM had been separating storage and compute in the
"DuckDB in Action" includesMotherDuck is pleased to offer this free PDF of the Manning “DuckDB in Action” book by Mark Needham, Michael Hunger and Michael Simons. This is the complete text. The first few chapters should help you understand the basics of DuckDB and getting started with SQL. The book also covers advanced data analytics with SQL, building data engineering pipelines with DuckDB, DuckD
If you haven't had the chance to get up to speed with DuckDB, this tutorial is for you! We'll go over the essentials, from installation to workflow, getting to know the command-line interface (CLI), and diving into your first analytics project. If are too lazy to read, I also made a video for this tutorial. Let's start quacking some code! Editor's note: this tutorial was originally published 2023-
What do Joe Reis, Holden Karau, Adi Polak, Benn Stancil, George Fraser have in common?Find out
For more than a decade now, the fact that people have a hard time gaining actionable insights from their data has been blamed on its size. “Your data is too big for your puny systems,” was the diagnosis, and the cure was to buy some new fancy technology that can handle massive scale. Of course, after the Big Data task force purchased all new tooling and migrated from Legacy systems, people found t
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