Hi Cal (and all others),
From what I can tell, you want to run a copy of the database on
multiple mini devices and have replication between them?
I think I've actually made myself not perfectly clear. My plan would be to have a local portable django server for letting all the tablets in a LAN (the only clients existing for it) access this local central information repository even when an outside internet connection is not available and let this portable server sync to the central remote storage whenever it can reach it. At the same time someone from the outside might edit the very same models directly in the remote repository. An automatic mechanism would be in place to compute deltas and merge changes from both: once over, both DBs would have the same data inside.
If so, this
isn't really a good use case for replication, and adds several
unnecessary layers of complexity.
Even though starting from preconditions not totally matching with the real use case, this conclusion equally holds true ;-)
So lets look at the end goal, you
want multiple clients to have read/write access to the same data, with
the constraint that the internet connection will be unreliable, but
you still want the data to be accessible, and possibly, editable.
Exactly.
This can be easily achieved by implementing good development
practises,
[...]
simple and clean
implementation of such a structure.
I'm not sure I see the connection here. Native mobile apps and/or html5 clients can leverage local storage strategies to be properly synchronized as soon as the connection is available. This would totally make sense in a context in which each CUD (not considering read here, since it's not much of a problem) operation is related to "personal non-shared" data only. The problem, here, is that more than one client will almost always perform some modifications to the same models, so your next point is not an exception, it's the rule.
To achieve this, you also have to consider conflict handling, for
[...]
quite simple, at least once you get past all the academic stuff, the
hard part is exposing it to the user in a friendly way.
And this is exactly the problem I'm trying to face here. My original purpose was to understand whether there's any out-of-the-box solution managing a "dual-master" synchronization in django.
I found this [1], but besides requiring a patch to the Postgres 9.4 code base, is not yet considered production-ready.
You can get around many of these problems by disabling edits unless
there is an internet connection, allowing only read access in the
event of a connection drop out, then using model caching on the client
side (along with a bulk retrieve request).
By using a local django repository (local meaning within the local wireless network among the tablets) I would get totally rid of the synchronization and notifications problems among all the native and/or html5 clients, moving the synchronization problem between the two databases only (the local and the remote one). Whether this would be an actual improvement or not, I'd have some more experienced user to decide.
However both approaches
come with the same problem of delta changes, if a model changes then
each app will need to be notified about this, ideally via a push
mechanism.
I am not an expert in this field and I'm afraid it would require a lot of time to design a proper merging mechanism.
Designing an events system around this can be quite
challenging, for even the most seasoned developers.
I get that.
If you have enough time/resources then it could be a fantastic
learning experience for you, but if this is a quick/dirty project
primarily lead by billable hours, then you probably don't want to
follow this route. If someone sent me a spec like this, I'd say it
would *easily* be 300+ hours work.
I'd like a quick and clean solution here ;-), since I have not enough time to follow all the required learning curve but I will be required to maintain and improve this project, so I'd rather pick a scalable solution from the beginning.
Hope this helps, if I have misunderstood, let me know.
It helps a lot, thanks for your time!
B.
[1] https://wiki.postgresql.org/wiki/BDR_User_Guide
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