This is some interesting shit, I love it! At least that parts I think I understand :P
> The goal of data versioning is to provide more mechanisms for library authors to evolve their schemas without imposing breaking changes often. Application developers will have limited use of this feature, as they would rather update their existing codebases and their types right away. Although this may find use cases around durable data and distributed systems.
"Hard cutover" is definitely a lot less laborious, but often times incremental updates are necessary - large teams, existing tables and whatnot. To that end, I would foresee a lot of appeal in app dev when applied to database migrations.
Yeah, it’s a non-starter in a lot of ways. I’m working on an alternate implementation that uses fragments, enabled by ongoing updates to ParadeDB’s syntax. Gonna explore all options and see where the cards land.
> The goal of data versioning is to provide more mechanisms for library authors to evolve their schemas without imposing breaking changes often. Application developers will have limited use of this feature, as they would rather update their existing codebases and their types right away. Although this may find use cases around durable data and distributed systems.
"Hard cutover" is definitely a lot less laborious, but often times incremental updates are necessary - large teams, existing tables and whatnot. To that end, I would foresee a lot of appeal in app dev when applied to database migrations.