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I'm trying to find the right database service to use. I need multiple computers (1-5) to be able to access/write/read to the database simultaneously, locally (without internet access, via connecting the computers to each other with cables). If I needed an extra computer to sit on the side and host the server while the others connect to it, that's fine.

The idea is that a relatively small database will be created during data collection (offline), each time we collect data, then merged with a master database at a later time to store it all. Sort of like creating a MS Access file and putting the data in it every time, but using something other than Access. My first thought was to have the computers writing to a SQLite3 database but that runs into concurrency issues and record locking with writing. I'm now considering MySQL, but wanted other opinions.

Ideally the data is able to be pulled directly into LabVIEW for analysis / making GUIs that utilize the data, etc, which I know most DBMS are compatible with. However I'd also like to take all the data I currently have (which is stored as text files in many directories) and write a python script to insert it all into the master database. I'm not sure if any databases restrict that capability, but it's something to consider.

Thanks for any input.

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    I am sorry but offline data collection and later merging is a bad idea, as it created thousand of problems because of conflicts and will cost you in the end days of work and a lot headache. Better just use one of the common server-based databases (MySQL/MaraiaDB, Postgres, MSSQL, MongoDB, CounchBase, ..) and host a small server in your LAN. No internet needed, just the LAN.
    – Robert
    Jun 17, 2022 at 17:03
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    @Robert Offline data collection is not only a good idea if you can't ensure connectivity, but also very frequently done. You need to take replication into account, but once done merging isn't a really difficult process. Of course, not having to do it if possible is even better.
    – Alejandro
    Jun 22, 2022 at 12:32

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