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Expand Up @@ -792,7 +792,7 @@

00:21:04 Oh, wow.

00:21:04 There's a community extension to read BigQuery.
00:21:04 There's a community extension to read Big Query.

00:21:06 So it's really a universal Swiss Army knife in a lot of ways to read from those operational data stores, but to do those analytical tasks.

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00:27:42 So one key note, if folks really know a lot about SQLite, one of the defining characteristics of it is that it is very much non-typed as much as possible.

00:27:50 VectDB is very much more traditional in that it does have typing.
00:27:50 Vector DB is very much more traditional in that it does have typing.

00:27:55 It does take full advantage of having nice numeric data types, date times that are true date times, not strings.

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00:28:46 It's worse than that.

00:28:49 But DuckTB is okay and ready to handle it and making it easy.
00:28:49 But DuckDB is okay and ready to handle it and making it easy.

00:28:54 Because it really aligns with the DuckTB ethos, which is a database shouldn't be extra work.
00:28:54 Because it really aligns with the DuckDB ethos, which is a database shouldn't be extra work.

00:28:58 It should be saving you work.

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00:41:08 So AWS, Google, Azure, you can read individual files or actually it'll understand hierarchies of files.

00:41:15 So if you have like a top level folder for a year and a folder for month and day, if you filter for I only want three days worth of data, DuckTB will only read three files.
00:41:15 So if you have like a top level folder for a year and a folder for month and day, if you filter for I only want three days worth of data, DuckDB will only read three files.

00:41:24 So it's pretty slick.

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00:48:57 All right.

00:48:57 You gotta have fun with it.
00:48:57 You got to have fun with it.

00:48:59 Right.

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00:49:38 And the reason for that is you no longer need 50 servers to answer your questions.

00:49:43 It turns out laptops are pretty daggone fast now.
00:49:43 It turns out laptops are pretty Dagon fast now.

00:49:45 Yeah.

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01:01:39 Now get out there and write some Python code.

01:01:41 You You you you Thank you.

01:01:41 You Thank you.