Well actually we do infer directly from the Postgres schema. Only for users not familiar with Postgres directly, we recommend going through the UI so that not only is the table created, but the Data API is also asked to track it and provide an API for it.

There is other metadata that we do need the user to specify, via the UI or the API, and that's for stuff like permissions and relationships.

Regarding, the unrestricted querying, we address it in one of the following ways:

1. Timing out queries running for longer than a specified interval.

2. Cursors and streaming data if the dataset requested is large.

3. Query templates: We allow the developer to create a RESTful API endpoint that has a limited pre-defined surface area (eg: GET data.mysite.com/v1/template/article?limit=10) which internally maps to a pre-defined query.

Our docs are still lagging behind on these unfortunately!

What do you guys do to restrict access? Any suggestions?

timing out - it works up to a point, if you for example set a hard limit to 1s then to an attacker it just means he needs to do a few parallel requests and he still kills your db.

what postgrest does for protection: a - no fancy joins, joins are only done by a thing we call "embedding" and those are joins between tables that FKs defined between them so they are fast, if you need fancy joins then the user has to define the view doing the join and expose it to the api.

b - no functions applied to the return columns, like you cant generate something like "select md5(bigtextcolumn) ..."

c - the only way to "kill" the database under postgrest is to use a filter on a column that has no index ( name like "hello"), out of the box postgrest does not have protection build in for that, but it's easy to put a proxy in front and whenever there is a url parameter called "name" you just reply with "you are not allowed to filter by this column"

> about metadata: in Postgrest ..

We don't want to restrict the data service to a particular schema. You can add a table from any schema to be tracked, say information_schema or pg_catalog. In fact, that is how introspection works (you can look at the queries made by the console). This means that the schema cache in memory would be quite large because of the number of tables in information_schema/pg_catalog if we were to auto load all these. There is also the issue that you may not want to expose some tables. We can definitely have a console button which will let you import all the tables in public schema.

Sure, you can infer relationships from the foreign key constraints. But, how would you come up with names that do not conflict with the existing columns? What if you add a new column with the same name as an inferred relationship? With the data service, you can also define relationships on/to views across schemas (1). Making metadata explicit goes with one of our core principles, 'no magic'.

> what postgrest does for protection: a - no fancy joins,

explicit joins are not allowed even with our data service. The joins that happen are the implicit ones because of the relationships. We do the same thing if we need any custom joins/aggregations. Define a view and expose it.

> b - you can't do anything other than selecting columns and relationships with the api.

> c - the permission layer can be used to prevent these to some extent (like not allowing an anonymous user to filter on a particular column).

1. https://hasura.io/_docs/platform/0.6/getting-started/5-data-...

- b,c that's good that you don't expose the entire SQL

also there is a way to do it in a single query but that is not yet implemented in postgrest

I guess it might be convenient to do this (determine relationships across views), but the users should be aware of the guarantees offered in this scenario.

True. That would also mean creating a database user for every application user. The auth service needs to attach more metadata to the users and since postgres does not allow you to reference system catalogs, the two user systems have to be kept in sync. We were not quite certain how this idea of mapping users would pan out when we started building the auth service.