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Remote Postgres to Postgres data

I am working on a project now where I need to load daily data from one psql database into another one (both databases are on separate remote machines).
The Postgres version I'm using is 9.5, and due to our infrastructure, I am currently doing this using python scripts, which works fine for now, although I was wondering:
Is it possible to do this using psql commands that I can easily schedule? or is python a flexible enough appproach for future developments?
EDIT:
The main database contains a backend connected directly to a website and the other contains an analytics system which basically only needs to read the main db's data and store future transformations of it.
The latency is not very important, what is important is the reliability and simplicity.

sure, you can use psql and an ssh connection if you want.
this approach (or using pg_dump) can be useful as way to reduce the effexcts of latency.
however note that the SQL insert...values command can insert several rows in a single command. When I use python scripts to migrate data I build insert commands that insert up-to 1000 rows, thus reducing latency by a factor of 1000,
Another approach worth considering is dblink which allows postgres to query a remote postgres directly, so you could do a select from the remote database and insert the result into a local table.
Postgres-FDW may be worth a look too.

Are SQLite reads always hitting disk?

I have a Pylons application using SQLAlchemy with SQLite as backend. I would like to know if every read operation going to SQLite will always lead to a hard disk read (which is very slow compared to RAM) or some caching mechanisms are already involved.
does SQLite maintain a subset of the database in RAM for faster access ?
Can the OS (Linux) do that automatically ?
How much speedup could I expect by using a production database (MySQL or PostgreSQL) instead of SQLite?

Yes, SQLite has its own memory cache. Check PRAGMA cache_size for instance. Also, if you're looking for speedups, check PRAGMA temp_store. There is also API for implementing your own cache.
The SQLite database is just a file to the OS. Nothing is 'automatically' done for it. To ensure caching does happen, there are sqlite.h defines and runtime pragma settings.
It depends, there are a lot of cases when you'll get a slowdown instead.

How much speedup could I expect by using a production database (Mysql or postgres) instead of sqlite?
Are you using sqlite in a production server environment? You probably shouldn't be:
From Appropriate Uses for Sqlite:
SQLite will normally work fine as the database backend to a website.
But if you website is so busy that you are thinking of splitting the
database component off onto a separate machine, then you should
definitely consider using an enterprise-class client/server database
engine instead of SQLite.
SQLite is not designed well for, and was never intended to scale well; SQLite trades convenience for performance; if performance is a concern, you should consider another DBMS

Database for Python Twisted

There's an API for Twisted apps to talk to a database in a scalable way: twisted.enterprise.dbapi
The confusing thing is, which database to pick?
The database will have a Twisted app that is mostly making inserts and updates and relatively few selects, and then other strictly-read-only clients that are accessing the database directly making selects.
(The read-only users are not necessarily selecting the data that the Twisted app is inserting; its not as though the database is being used as a message-queue)
My understanding - which I'd like corrected/adviced - is that:
Postgres is a great DB, but almost all the Python bindings - and there is a confusing maze of them - are abandonware
There is psycopg2 for postgres, but that makes a lot of noise about doing its own connection-pooling and things; does this co-exist gracefully/usefully/transparently with the Twisted async database connection pooling and such?
SQLLite is a great database for little things but if used in a multi-user way it does whole-database locking, so performance would suck in the usage pattern I envisage; it also has different mechanisms for typing column values?
MySQL - after the Oracle takeover, who'd want to adopt it now or adopt a fork?
Is there anything else out there?

Scalability
twisted.enterprise.adbapi isn't necessarily an interface for talking to databases in a scalable way. Scalability is a problem you get to solve separately. The only thing twisted.enterprise.adbapi really claims to do is let you use DB-API 2.0 modules without the blocking that normally implies.
Postgres
Yes. This is the correct answer. I don't think all of the Python bindings are abandonware - psycopg2, for example, seems to be actively maintained. In fact, they just added some new bindings for async access which Twisted might eventually offer an interface.
SQLite3 is pretty cool too. You might want to make it possible to use either Postgres or SQLite3 in your app; your unit tests will definitely be happier running against SQLite3, for example, even if you want to deploy against Postgres.
Other?
It's hard to know if another database entirely (something non-relational, perhaps) would fit your application better than Postgres. That depends a lot on the specific data you're going to be storing and the queries you need to run against it. If there are interesting relationships in your database, Postgres does seem like a pretty good answer. If all your queries look like "SELECT foo, bar FROM baz" though, there might be a simpler, higher performance option.

There is the txpostgres library which is a drop in replacement for twisted.enterprise.dbapi, —instead of a thread pool and blocking DB IO, it is fully asynchronous, leveraging the built in async capabilities of psycopg2.
We are using it in production in a big corporation and it's been serving us very well so far. Also, it's actively developed—a bug we reported recently was solved very quickly.
http://pypi.python.org/pypi/txpostgres
https://github.com/wulczer/txpostgres

You could look at nosql databases like mongodb or couchdb with twisted.
Scaling out could be rather easier with nosql based databases than with mysql or postgres.

Real-time SQLite and PostgreSQL bi-directional synchronization using python

Is there any python library that can keep a client-side SQLite database in sync with a server-side PostgreSQL database?
There are solutions for Java, such as Daffodil or SymmetricDS. Is there something similar for python?

SymmetricDS is a server-side solution for synchronization that gets triggered regardless of which language is being used to access the database. You should still be able to use that to synchronize the databases, while using Python libraries to actually query them. I would recommend sqlalchemy as a good database-independent query layer for Python.

Multi-Threaded data insertion in MySQL using python

I am working on a project involving insertion a lot of data in to the database. I am wondering if anybody knows how to fill 2 or 3 tables in the database at the same time.An example or psueodecode would be helpful.
Thanks

If you have a lot of data to insert into the database all at once, then you probably are interested in bulk loading data. The ideal tool for that is the bulk loader that likely comes with your database -- Oracle, Microsoft SQL Server, Sybase SQL Server, and MySQL (to name the ones that come to mind) all have bulk loaders. For example, Microsoft has the bulk insert statement and the bcp program to perform this task. I recommend you look into that rather than rigging up some tool in python, with or without threads.