... exactly that: shipped the entire result set to the browser and let it sort itself out. Same deal for Spanner. A lot of Basedash is just "run the SQL the user wrote, show the rows." We support 10+ dialects (Postgres, MySQL, BigQuery, Snowflake, Athena, SQL Server, Spanner, and friends), and every query gets paginated because we can't stream a 12M row result set to a browser. For years the approach was wrap-and-pray. Take whatever the user wrote ... ... OFFSET 200; The nice thing about this is the query stays opaque. You don't have to understand its grammar to paginate it, which is exactly why it shipped fast and lasted years. It works great on the easy dialects

... understanding what kind of SQL flavor your database is using . Think of it like this: most tools speak generic SQL. But Text2Query now understands the nuances effortlessly switching between different SQL flavors and MongoDB , like someone fluent in multiple dialects. Now, when you upload a schema, the app automatically detects whether it s PostgreSQL, MySQL, SQL Server, or MongoDB , and adapts the queries and syntax accordingly. Just upload your schema. Text2Query detects the dialect

... Reda Halib(@alexredahalib): Already applied with lessan. We're building sovereign AI infrastructure for banks in emerging markets, starting with Morocco. The problem is simple: US cloud AI is illegal for core banking (data sovereignty laws) and broken on dialects, GPT hallucinates on Darija (Moroccan dialect