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What if dimensions and measures were rows instead of columns? Introducing KC Star, a PostgreSQL data warehouse I evolved through nine versions, starting with the inverted foundation - SCD2 history, SHA-256 fingerprints and time travel included.
The read side of archive-on-delete: querying archives through promoted typed columns, digging into jsonb payloads for everything else, polling snapshots with a 202 pattern, and an honest accounting of the restore path ArchiveKit doesn't have yet. Part 9 wraps up the Archive-on-Delete with ArchiveKit series.
The storage design behind ArchiveKit - typed queryable columns and a jsonb payload from a single write, why the archive's EntityId is an index but deliberately not a foreign key, and the reflective model configuration that builds every archive table from one method call. Part 4 of the Archive-on-Delete with ArchiveKit series.
Hard deletes destroy the audit trail; soft deletes clutter live tables forever. Introducing ArchiveKit, a .NET library that intercepts deletions and stores immutable archive snapshots with TTL policies and cascade archiving.
Archive tables are meant to empty out - a background worker migrates their rows into the current table while live traffic reads and write-through updates race it. This part walks the EF backfill's insert-then-conditional-delete choreography and the timestamp that keeps it honest. Part 9 of the Entity Versioning with VersionKit series.
A point lookup that might hit any of three tables, a list query that should span them all, and writes that must keep a registry honest - this part walks VersionKit's version-aware reader and writer, and the generated UNION view that makes every schema era queryable as if it were current. Part 8 of the Entity Versioning with VersionKit series.
JSON payloads can migrate lazily because the reader controls the shape - relational rows cannot, because the table is the shape. VersionKit's EF Core answer is table-per-version - archive Orders as Orders_v2 on a schema bump, track every row's home in a registry, and let old rows stay old until something moves them. Part 7 of the Entity Versioning with VersionKit series.
Nine parts of architecture posts lie by omission unless the tenth is the ledger. What earned its keep — isolation as data, MaxTenants = 1, the schema-keyed model cache — and the honest list of shortcuts: plaintext connection strings, cache windows, reflection, and a fan-out loop that still says TODO.
Seven parts of migration machinery existed to deliver one table — a hierarchical crumb trail with three ltree columns, a jsonb payload, GiST and GIN indexes, and a Dapper read side that speaks PostgreSQL's native operators. This is why it was PostgreSQL all along.
Deleting a tenant is the most dangerous button in the platform — behind it sit DROP SCHEMA CASCADE and DROP DATABASE. A two-step lifecycle with global query filters, a SaveChanges interception and an explicit purge keeps the blast radius survivable.
A signup click becomes a real PostgreSQL database or schema in seconds. Running CREATE DATABASE from application code feels illegal until you contain it — identifier validation, quoted DDL, idempotent steps, and a status machine that admits when provisioning fails.
EF Core wants one database, one model and one migrations history table. Schema-per-tenant breaks all three assumptions. Constructor-injected migrations, a per-schema history table and a replaced IMigrationsAssembly put one migration set in charge of every tenant schema.
Database-per-tenant, schema-per-tenant, or packed into a shared database? Kicking off a series on building a multi-tenant platform where one EF Core codebase supports all three isolation strategies behind a single control plane.
