When you claim that you are not using an ORM, a reasonable person would take it to mean that you are forgoing the use of query builders and automated mapping from SQL results to application data structures.
So, it may be true that classifying these libraries as ORMs is incorrect, but the "user experience" as a developer between these libraries and typical ORMs appears to be pretty much the same. Or is that unfair?
AR/Django encourage you to describe your entire schema, _including_ the relationships between tables, as attributes on your model objects. Upon doing this, you get simple and reliable programmatic access to some basic access and storage patterns.
Using this knowledge of your data model, the ORM can now provide you with more advanced tools: it can automatically join across tables (`select_related`), lazily load dependent data, generate SQL schema for you, transparently cache queries, automatically provide HTML form validators, and even automate database schema migration for you. The more completely you model the system, the more it can do for you.
In these systems, the database is subservient to the model. This is a problem, because the database is reality and the model is a model.
Dropping to "opaque SQL strings" is discouraged, both because it's considered error prone ("You should leave SQL to the professionals! There are lots of eyes on this!") and because there is often no graceful way to integrate custom query code with your model layer; instead, you investigate how to do so within the confines of the ORM. For every case where you can eventually find what you need (`select_related("user__friends__email")`), there are a dozen where you can't.
People start writing things in application code that could be handled easily and more efficiently by the database: aggregations are a classic, since ORMs support is either missing or incredibly complex. As soon as the application becomes non-trivial, the problems magnify. They don't do this because they are stupid, or bad developers, they do this because it's what the tools encourage: they encourage simplistic CRUD access and mistrust/suspicion/fear of SQL.
SQLAlchemy is quite different from this, because its primary focus is to model databases, not to provide some kind of declarative object language with its own set of semantics that do not exist in SQL.
Because Go can't do things like meta classes or creating/modifying types at runtime, a lot of this simply isn't there, even though people want it.
Sqlx does like 2 things; it adds named query parameter support, and it marshals rows into structs. Squirrel is just a query builder. The whole philosophy that the database must somehow be modeled and that access to the database is done via that model is absent.
 This is especially durable tarmac with which to pave your road to hell.
 This can mean "lots of requests", or "complex schema", or "complex reporting requirements"... all sorts of things.