alt Hacker NewsI work on geospatial apps and the software I think I am most excited about is https://felt.com/. I want to see them expand their tooling such that maps and data source authentication/authorization was controllable by the developer, to enable tenant isolation with proprietary data access. They could really disrupt how geospatial tech gets integrated into consumer apps.
This article doesn't acknowledge how niche this stuff is and it's a lot of training to get people to up to speed on coordinate systems, projections, transformations, etc. I would replace a lot of my custom built mapping tools with Felt if it were possible, so I could focus on our core geospatial processes and not the code to display and play with it in the browser, which is almost as big if not bigger in terms of LOC to maintain.
As mentioned by another commenter, this DuckDB DX as described is basically the same as PostGIS too.
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Author here: the beauty of DuckDB spatial is that the projections and CRS options are hidden until you need them. For 90% of geospatial data usage people don't and shouldn't need to know about projections or CRS.
Yes, there are so many great tools to handle the complexity for the capital-G Geospatial work.
I love Felt too! Sam and team have built a great platform. But lots of times a map isn't needed; an analyst just needs it as a column.
PostGIS is also excellent! But having to start up a database server to work with data doesn't lend itself to casual usage.
The beauty of DuckDB is that it's there in a moment and in reach for data generalists.
Have you tried https://geobase.app/ they recently also had a post about duckdb integration: https://geobase.app/blog/duckdb-1-1-3
I was just about to get into Felt then they took away the free tier and made it very expensive.
> it's a lot of training to get people to up to speed on coordinate systems, projections, transformations, etc
This can mostly be avoided entirely with a proper spheroidal reference system, computational geometry implementation, and indexing. Most uses of geospatial analytics are not cartographic in nature. The map is at best a presentation layer, it is not the data model, and some don’t use a map at all. Forcing people to learn obscure and esoteric cartographic systems to ask simple intuitive questions about geospatial relationships is a big part of the problem. There is no reason this needs to be part of the learning curve.
I’ve run experiments on unsophisticated users a few times with respect to this. If you give them a fully spheroidal WGS84 implementation for geospatial analytics, it mostly “just works” for them anywhere on the globe and without regard for geospatial extent. Yes, the software implementation is much less trivial but it is qualitatively superior UX because “the world” kind of behaves how people intuit it should without having to know anything about projections, transforms, etc. And to be honest, even if you do know about projections and transforms, the results are still often less than optimal.
The only issue that comes up is that a lot of cartographic visualization toolkits are somewhat broken if you have global data models or a lot of complex geometry. Lots of rendering artifacts. Something else to work on I guess.