Skyscraper is the code-first ORM inside BizBlocks. One C# class gives you a table, an audit trail, tenant isolation, caching, and schema documentation your AI agents can actually read.
Migrations drift from the code. Nobody remembers which columns mean what. Tenant filtering gets forgotten in one query and leaks data. Audit fields get bolted on late. Caching becomes guesswork.
Skyscraper handles all of it as a property of the entity, not as work you remember to do.
// Business meaning, readable by tooling and AI
[Display(Name = "Reservation",
Description = "A booked storage unit")]
[TableMapping("dbo.Reservation")]
public class Reservation : skyClass<Reservation>
{
[PrimaryKeyColumn, IdentityColumn]
public int Id { get; set; }
public Guid CompanyKey { get; set; }
public string Name { get; set; }
[Encrypted]
public string TaxId { get; set; }
}
// Fluent, tenant scoped, cached
var open = Reservation.Query()
.WithCurrentCompanyKey()
.WithValue("Status", "Open")
.Cached()
.ToList();The database is generated from your classes and version controlled with your application. Schema changes are refactors, not migration archaeology.
Created and modified timestamps and the acting user are tracked on every record, with row-level change history available through the audit module.
A company key isolates each tenant, with hierarchy down through departments, users and individual resources.
Multi-tier Redis and in-process caching with explicit invalidation, opted into per query rather than guessed at.
Mark a property as encrypted and sensitive values are protected at rest without touching your query code.
Display names, descriptions, relationships, validation and usage context travel with the entity, which is what makes the MCP server useful.
Your core data lives in SQL Server or MySQL. Reporting can additionally target other stores, so a single view can span systems.
The primary store for BizBlocks applications.
Fully supported as a primary or reporting source.
Document data, queryable from the reporting engine.
Document collections as a reporting source.
Warehouse queries alongside operational data.
Distributed caching and SignalR backplane.
Search and log analytics.
Flat file and SFTP sources for imports.
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