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The goal is to have a convenient API to work with common data structures, with an SQL backend and all the benefits it provides. Such as:

— Small memory footprint even for large datasets.

— ACID transactions.

— SQL interface for introspection and reporting.

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So the goal is to have a Redis-like API but not actually be an in-memory data store and reduce memory consumption this way? For example, for a project/service that started with Redis, but then priorities shifted and small memory footprint became more important than performance? Did I get it right?

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