I looked into Datasette before starting ROAPI. From a product/use-case point of view, to me Datasette focuses more on quick and easy ad-hoc data exploration type of work. ROAPI focuses more production ready online serving of static datasets. So I would expect users to use ROAPI to power micro-services in production with high QPS.
From a technical design point of view, ROAPI authors owns the full stack end to end from query parsing, data format parsing to query execution because I am also a maintainer of Apache arrow and it's sub-project datafusion. The whole project is built with Rust end to end from scratch. Datasette is mostly a wrapper around sqlite. It translates user actions into SQL queries, then execute them on sqlite. In ROAPI, we work at a lower level. We translate REST APIs, GraphQL and SQLs into datafusion logical plans and execute them. Datafusion is also a analytical compute engine optimized for columnar data, so it will be a lot faster for OLAP workload, while sqlite is optimized for OLTP. I also plan to add other type of query capabilities like nearest neighbor vector search for ML applications, etc.
From a technical design point of view, ROAPI authors owns the full stack end to end from query parsing, data format parsing to query execution because I am also a maintainer of Apache arrow and it's sub-project datafusion. The whole project is built with Rust end to end from scratch. Datasette is mostly a wrapper around sqlite. It translates user actions into SQL queries, then execute them on sqlite. In ROAPI, we work at a lower level. We translate REST APIs, GraphQL and SQLs into datafusion logical plans and execute them. Datafusion is also a analytical compute engine optimized for columnar data, so it will be a lot faster for OLAP workload, while sqlite is optimized for OLTP. I also plan to add other type of query capabilities like nearest neighbor vector search for ML applications, etc.