metagration VS assert-combinators

Realtime uses logical replication, and from your link it looks like it should work with Timescale (although not recommended):

> Using logical replication with TimescaleDB is not recommended, as it requires schema synchronization between the primary and replica nodes and replicating partition root tables, which are not currently supported.

As long as logical replication is supported, this won't be an issue for Realtime because the purpose is to receive data changes (which come in a JSON format) and the end-user doesn't need to persist schema modifications.

> but couldn't get it working

If you send me some error logs, I can take a look or forward to one of the team.

> support Postgres streaming replication

This is the first time I've heard it requested - I don't think it's something we'd do unless there was a good reason and strong demand. If we were to do any work in this direction we'd prefer to try contribute DDL streaming to PostgreSQL's logical streaming. We've been thinking about this for a while (Michel has built metagration - https://github.com/michelp/metagration which has prompted a few ideas for core patches)

We use in prod variant of no 1. [0]. Why? Because:

* it's extremely lightweight (built on pure, functional combinators)

* it allows us to use more complex patterns ie. convention where every json field ends with Json which is automatically parsed; which, unlike datatype alone, allows us to create composable query to fetch arbitrarily nested graphs and promoting single [$] key ie. to return list of emails as `string[]` not `{ email: string }[]` with `select email as [$] from Users` etc.

* has convenience combinators for things like constructing where clauses from monodb like queries

* all usual queries like CRUD, exists etc. and some more complex ie. insertIgnore, merge1n etc has convenient api

We resort to runtime type assertions [1] which works well for this and all other i/o; runtime type assertions are necessary for cases when your running service is incorrectly attached to old or future remote schema (there are other protections against it but still happens).

[0] https://github.com/appliedblockchain/tsql

[1] https://github.com/appliedblockchain/assert-combinators

We use not so much frameworks but combination of lightweight libraries:

- runtime assertions [0] - to map unknown values at i/o boundary into statically typed code (rpc input parameters, sql results etc)

- template based sql combinators to sanitize sql/generate sql [1]

- jsonrpc over websockets - for bidirectional comms between f/e and b/e

[0] https://github.com/appliedblockchain/assert-combinators

[1] https://github.com/appliedblockchain/tsql

Types can be asserted at runtime (parsed) at IO boundaries (reading http request or response, websocket message, parsing json file etc). Once they enter statically type system they don't need to be asserted again.

The difference it makes is illusion of type-safety vs type-safety this article touches on.

You can try to bind service with client somehow but in many cases this will fail in production as you can't guarantee paired versioning, due to normal situations by design of your architecture or temporary mid-deployment state or other team doing something they were not suppose to do etc. It's hard to avoid runtime parsing in general.

Functional combinators [0] or faster [1] with predicate/assert semantics work very well with typescript, which is very pleasant language to work with.

[0] https://github.com/appliedblockchain/assert-combinators

[1] https://github.com/preludejs/refute

Once i/o boundaries are parsing unknown types into static types, your type safety is guaranteed.

[0] https://github.com/appliedblockchain/assert-combinators