I saw this blog post,
That's a blog from the creator of PostgreSQL, so you have to take what he writes understanding that he's writing from a very PostgreSQL-centric perspective. For example, this: Where the database is replacing a collection of GeoTIFF imagery files, it is probably false. Raster in the database will be slower, will take up more space, and be very annoying to manage.
It would be more accurate to say "Raster in the database will be slower, if you are using PostgreSQL." PostgreSQL is notoriously slow with rasters. If you're using a database, like Manifold, which is fast with rasters, you don't have those downsides. Rasters in Manifold tend to be faster, they take up only slightly more space (and sometimes less), and they're not at all annoying to manage. In fact, they're much easier to manage than in most formats. I always import rasters into the .map file, and I routinely work with rasters in the 20 GB to 100 GB range. I don't find that they inflate the .map file all that much compared to original formats like GeoTIFF. In exchange you get huge flexibility and way more capability. For example, suppose I have a 100 GB GeoTIFF that shows terrain elevation data for a continent in reasonably high resolution. I can create images with 20 different stylings of that data for zero extra size (they all take their data from the same table) to show different combinations of palettes and hill shading options. Each one of those different stylings can be used as a layer. Also wondering if the round tripis worth the time savings: if Manifold can perform a raster operation in 2 minutes vs. 10 minutes in QGIS,
Round trip time to import and export is only something to consider if you're using Manifold as an editor for data that you're forced to keep in some other format, and at that it's the tail end of what could be a very long pipeline of workflow. I keep my data in Manifold .map format because nothing else comes close to the speed and convenience of the format: pop open a 200 GB project in 1/2 second, and all that. You can also link in hundreds of GB from other projects and it's just as fast as having it all in the same project, even if your constellation of data is over a terabyte. It also depends what you're doing with the rasters. If your analytics involve any of hundreds of operations that can use GPU effectively, you're typically looking not at 2 minutes in Manifold vs. 10 minutes in Q, you're looking at 5 or 10 seconds in Manifold vs. 10 minutes in Q. That's a big win even if you're stuck with eventually writing the data out to some ancient, slow format. It's true that keeping everything in Manifold format means a one-time cost of time to import really huge files into Manifold. But that's true of every high performance environment. If you're doing HADOOP or other parallel work in the cloud, you have to upload your data into that cloud before you can do anything. But once your data is in Manifold, everything becomes so convenient and fast. I don't even bother checking data sizes anymore, and I routinely use 10 GB and 20 GB raster layers just because I have them on hand and I like the way they look in my projects.
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