You are not avoiding it. You are making an entire DB to mimic garbage collection because you don't have garbage collection. I fell like I am the one avoiding everything you went through to make it.
And I am happy you are doing it. I really do. All I am asking is this discussion is to provide performance indicators that allows us to compare the complete performance with other stacks.
If I compare my cache with your DB already in memory, the performance is exactly the same. Mine might be slower because it is full thread safe for 1000s of reads and writes in the same millisecond. But that's it. Basically its the difference between B+ trees vs hash tables.
So, if I follow 500 people and use 5 Nostr apps, do you truly think duplicating 500 profiles in memory on each of those apps is an "efficient" use of memory?
Vitor Pamplona
npub1gc…fnj5z
2025-01-03 15:24:10
in reply to nevent1q…phkm
Author Public Key
npub1gcxzte5zlkncx26j68ez60fzkvtkm9e0vrwdcvsjakxf9mu9qewqlfnj5zPublished at
2025-01-03 15:24:10Event JSON
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"content": "You are not avoiding it. You are making an entire DB to mimic garbage collection because you don't have garbage collection. I fell like I am the one avoiding everything you went through to make it. \n\nAnd I am happy you are doing it. I really do. All I am asking is this discussion is to provide performance indicators that allows us to compare the complete performance with other stacks. \n\nIf I compare my cache with your DB already in memory, the performance is exactly the same. Mine might be slower because it is full thread safe for 1000s of reads and writes in the same millisecond. But that's it. Basically its the difference between B+ trees vs hash tables.\n\nSo, if I follow 500 people and use 5 Nostr apps, do you truly think duplicating 500 profiles in memory on each of those apps is an \"efficient\" use of memory?",
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