I haven't had issues in SedonaDB with savvy doing excessive rebuilds but I have no idea what the difference is (perhaps a less aggressive clean stragety?)
Posts by Dewey Dunnington
Positron plus JupyterHub logo, with the Posit logo in the corner.
We are thrilled to announce that Positron Server is now available for academic use via JupyterHub!
This gives students a robust #RStats & #Python data science IDE without needing a local install or new infrastructure.
Learn more: positron.posit.co/blog/posts/2...
Pretty sure you have to wrap it and duplicate the methods you want exposed (struct Wrapper { inner: Original }) but it's been a while!
That would be ST_2️⃣() (the PR has a full list 😀)
We heard you: ADBC is great, but you need it on mainframes.
Introducing ADBC for COBOL. The same connectors that work with Python, Rust, and Go now work with a language originally designed for punch cards.
columnar.tech/blog/adbc-co...
Can your current spatial SQL engine ST_💩()? We didn't think so!
As part of our ongoing attempt to innovate on spatial SQL in Apache Sedona, this we're proposing emoji shorthands for most functions which (1) improve expressiveness and (2) helps more SQL fit on one line.
Our list of 2026 #rstats and #python summer internships has been posted.
We can't wait to work with you and make great things!
tidyverse.org/blog/2026/03...
Kermit the frog screaming with excitement
We have summer internships y'all! Come work at Posit on the PyData, tidymodels, shiny, or Connect teams: grnh.se/tigz810a3us. You will have an awesome time, learn a ton, and help advance our open source and pro tools 🧰 #rstats #pydata
I tend to be a CRAN-appreciator. But wow, R-Universe is such a useful project.
As a developer, I can:
- Experiment with new and creative approaches that would never get accepted on CRAN;
- Have cross-platform binaries for my packages built within an hour (usually) of a GitHub push
An abstract hyperspace warp image inspired by the comedic "going plaid" effect from the 1980s cult film "Spaceballs".
The fastest operation is the one you don’t have to do.
When a database natively supports @arrow.apache.org, ADBC can speed up fetching and ingestion by eliminating costly row/column conversions.
How much faster is it in practice? We ran some benchmarks to find out. Link below 👇
Arctos Alliance (arctosalliance.org) is now officially launched!
"If your organization depends on Arrow or Parquet or you’re interested in helping sustain these critical data technologies, we would welcome a conversation about how to get involved."
Finally, we added the beginnings of an #rstats DataFrame API that can be used to implement a #dplyr backend. This is my favourite feature of SedonaDB 0.3.0 because I love R, dplyr, and because I never properly learned SQL 😬
#rstats users will be pleased to know that you can now read anything sf can piped directly into SedonaDB via GDAL's @arrow.apache.org integration. This makes the SedonaDB R package considerably more useful!
We also added a lot of functions (with full 4D and geometry type support with PostGIS integration tests, as usual!)
We've always had a great Parquet writer; however, Parquet is new on the block and sometimes you just need a Shapefile (or GeoPackage, or FlatGeoBuf). This was always possible with SedonaDB and pyogrio's Arrow integration but in 0.3.0 we gave it some nice defaults and made it easy to do.
Ever since reading @opencholmes.bsky.social's fantastic GeoParquet best practices guide, I've wanted to make that trivial to do with SedonaDB's Parquet writer. After this release...it is! Sort, compress, and reduce your row group size based on the results of any query all in one go!
One of the most commonly requested features by those of us who wrote SedonaDB code frequently was parameterized SQL queries! Now you can add a placeholder and bind just about any spatial object you can think of (CRS included!). Let us know if we missed your favourite one!
SedonaDB can now represent geometries with a separate CRS per row (like @postgis.bsky.social/EWKB), including transforming to and from with CRSes derived from a column. If you've ever been sent a spreadsheet with UTM coordinates with a "zone" column, this feature is for you!
The new spatial join gives more flexibility for running SedonaDB in memory constrained environments and increases the size of the data you can swing around on your laptop. It's currently opt-in (requires setting a memory limit)...give it a go and let us know how it goes!
We're chuffed to announce Apache SedonaDB 0.3.0! This release features a rewritten join that supports larger-than-memory spatial/KNN joins courtesy of Kristin Cowalcijk, new functions, parameterized SQL queries, GDAL/pyogrio reads, GDAL/sf based reads in R, and the beginnings of an R DataFrame API!
Does SedonaDB's KNN join help at all? I haven't wired up nice dplyrish syntax for everything yet but the SQL isn't too bad.
📖 Apache Parquet recently added native support for Geospatial. This post explains what that means and why it is important: parquet.apache.org/blog/2026/02...
Great inaugural post about the geospatial types on the Parquet blog.
Thank you Jia Yu, Dewey Dunnington , Kristin Cowalcijk, Feng Zhang.
More posts coming !
parquet.apache.org/blog/2026/02...
Released this week: Version 22 of the ADBC libraries and drivers.
This release includes updates to the ADBC libraries for 8 languages, and improvements to the 4 ADBC drivers that are maintained in the apache/arrow-adbc repository. See the blog for more details: arrow.apache.org/blog/2026/01...
Introducing gdalcli by Andrew Brown -- an R frontend to GDAL’s unified CLI (≥3.11) 🌐
Compose and execute GDAL workflows with pipe-friendly functions.
Learn more: github.com/brownag/gdal...
#RStats #GDAL #Geospatial #OpenSource #RSpatial
Apache SedonaDB 0.2.0 is now available. Download here: buff.ly/k9LRlyC
SedonaDB is the first open source, single-node analytical database engine that treats spatial data as a first-class citizen. It is developed as a subproject of Apache Sedona. #opensource