SedonaDB: A new geospatial DataFrame library written in Rust (sedona.apache.org)

Interesting, but why share the Sedona name?

I thought Apache Sedona is implemented in Java/Scala for distributed runtimes like Spark and Flink. Wouldn't Rust tooling for interactive use be built atop a completely different stack?

Was "written in Rust" really necessary?

What does it do besides being written in Rust?

Whats the point of this over polars?

Please don't use emojis in titles. Immediately looks like written by AI.

Somehow I dont see this applicable for 90% of all current spatial needs, where PostGIS does just right, and same IMHO goes for DuckDB. There perhaps exists 10% of business where data is so immense you want to hit it with Rust & whatnot, but all others do just fine im Postgre.

My bet is most of actually useful spatial ST_ functions are not implemented in this one, as they are not in the DuckDB offering.

I’ve been out of the geo loop for a while. I’m struggling to understand why I’d use this over postgis. There used to be the argument that installing extensions was painful, but now that docker exists pulling the postgis image is just as easy as normal Postgres. And RDS has supported it for a while.

What am I missing? The api even looks the same.

Question: Does SedonaDB support custom / alternative coordinate systems?

For example, if i wanted to define a 4d region called (fish, towel, mouse, alien) and there were floats for each of fish/towel/mouse/alien?

What is the advantage over Duckdb with Spatial Extension.

Everyone asking why this exists when DuckDB or PostGIS or the JVM based Sedona already exists, clearly has not run into the painful experience of working on these large geospatial workloads when the legacy options are either not viable or not an option for other reasons, which happens more often than you might expect! And the CRS awareness!!! Incredible! This is such a huge source of error when you throw folks that are doing their best, but don't have a lot of experience with GIS workloads. Very expensive queries have had to be rerun with drastic changes to the results, because someone got their CRS mixed up.

I don't get to do geospatial work as much anymore, but I would have killed for this just a year ago.

Looks interesting for more efficient geospatial operations. Congratulations!

is written in Rust a value add ? vs say Accessible not only via Python but first party support in Ruby, C#, Javascript ?

There is another great lib built on Apache Arrow - polars dataframe, which has amazing DSL.

It comes a disappointment for me that SedonaDB hasn’t adopted a similar approach.

Apache stack provides everything needed, but for small things I would not prefer SQL exactly

I found a simple way to be success, rewrite some exisinting project using rust!

PostGIS not being included in benchmarks got me suspicious