We are proud to sponsor Data Innovation Summit. Swing by booth D114 for a live demo from @mindspank.bsky.social & @jonwalls.dev. If you're interested in the following topics, let's meet up!

✅Fewer, better dashboards
✅BI-as-code
✅Real-time analytics
✅Reducing costs

www.rilldata.com/events/data-...

Next up is #DataInnovationSummit. If you're headed to Sweden in May, let's meet up and keep the good conversations flowing!

www.rilldata.com/events/data-...

Questions to ponder when you need to scale:
- When would you need to move beyond Postgres❓
- When do you need a specialized cloud data warehouse❓
- Is there an even better solution for low-latency dashboards or customer-facing analytics apps❓
- Can't we just use a fast database❓

I use ChatGPT from time to time to clean up code but it's just too slow. The 40s-1min it takes to clean up a component is enough distraction time that I flip to email, read slack, answer some DMs and then I completely forgot about it

With Trump axing the de minimis exception it will be very interesting to see the carbon impact it will have on the reduction in production and shipping. For being a republican he's very anti-globalism and consumerism

Rill is proud to sponsor DuckCon6 on Friday!

@medriscoll.com will also present on Rill's SQL-based metrics layer powered by @duckdb.org. Recognizing the wide popularity of SQL & DuckDB’s SQL dialect in particular, we developed a metrics layer that declares its metrics entirely with SQL expressions.

Been deep in shokupan and other Japanese bread videos lately. It's so interesting to see the divergence of kneeding techniques between western and asian bakers, same outcomes but widely different techniques. Something to learn!

Only 2.5 weeks until DuckCon #6 in Amsterdam.

We have a strong line-up: the presenters will explain how to use DuckDB for tabular, spatial and graph-shaped data, how to solve financial and healthcare use cases, and how to orchestrate and visualize queries.

Full program: duckdb.org/events/2025/...

We use @duckdb.org as the core engine for materializing Metrics Views, multi-dimensional OLAP cubes built on top of tables or files. At DuckCon6, @medriscoll.com will demonstrate how our metrics layer enables users to manage metrics with DuckDB’s SQL dialect ensuring uniformity across all dashboards

Will be in Amsterdam for #DuckCon at the end of January. Looking forward to seeing new use cases and what folks have been up to.

Perhaps the initial hype cycle is dying down and we start seeing the really valuable usecases emerge now

LLMs and a visualization grammer like Vega seems like a perfect fit for rapidly iterating on #visualizations

Anyone have done any fun work in this area?

I wrote a bit about this 7 months ago in a LI post:

"Running serverless SQL engines on object storage is 10x cheaper than running Spark on Delta Lake or DBT pipelines in Snowflake."

www.linkedin.com/posts/medris...