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Mar
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revised spatial database vs spatial datastructure?
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Mar
8
comment spatial database vs spatial datastructure?
Thanks for the response. I should have mentioned that i did the test on a client/server architecture, which means that the database is shared by other real-time applications, and that network latency affect test results, which is why i have repeated the tests multiple times. What might also affect the results is that in my scenario i queried for data (uids), whereas the other scenario queried for a number using the aggregate function count. I still am convinced that an in-memory solution (0.7s) is still much faster than one using the hard drive (2.3min), especially when data has to travel LAN.
Mar
6
revised spatial database vs spatial datastructure?
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revised spatial database vs spatial datastructure?
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revised spatial database vs spatial datastructure?
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revised spatial database vs spatial datastructure?
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Mar
6
answered spatial database vs spatial datastructure?
Mar
3
comment spatial database vs spatial datastructure?
Thanks. Yes, i've seen these posts as well, but they don't really answer my question in specific: "which is more performant when querying spatial bulkdata repeatedly in a batch"? I guess i'll just have to make a proof of concept myself, benchmark the results, and compare them next to each other.
Feb
26
comment spatial database vs spatial datastructure?
Geometric features are usually Points, (Multi)LineStrings, Polygons. LineStrings and Polygons can consist of up to 100 nodes, but are usually not that large.
Feb
26
comment spatial database vs spatial datastructure?
as for performance: the system would process the requests in batch at night, so it needs to finish its job preferably before users start using system resources. So if the difference between bulkloading everything into a datastructure would mean it can save up some serious processing time, it would be the preferred choice of method. In total about 10 tables are used, each containing over 1000 columns, and over 50 000 records.
Feb
26
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