"Shared data model" and "shared database schema" sound like the same claim and answer two different questions. One is about whether your CRM, finance, and HR systems read the same record instead of synced copies. The other is about whether different customers on a multi-tenant platform share underlying database structure. A platform can unify the first across engines while keeping the second strictly isolated, and the distinction matters more to a technical evaluator than either term alone.
What transactional integrity guarantees
Transactional integrity, formalized as the ACID properties, atomicity, consistency, isolation, durability, is a database guarantee about operations with multiple parts. Atomicity means the operation completes in full or leaves no trace of starting. Consistency means the database moves from one valid state to another, never a partial or contradictory one. Isolation means concurrent transactions do not corrupt each other. Durability means a completed transaction survives a system failure. None of this is specific to any vendor; it is the baseline a database has to meet for multi-step business operations to be trustworthy at all.
In practice, this is what makes "atomic where it matters" a real architectural claim rather than a slogan: a won opportunity creating its deal, project, and order as one transaction means all three exist or none do, with downstream finance notifications reacting only once that transaction has actually committed. Without that guarantee, a failure partway through can leave a deal marked won with no project and no order behind it, and nothing in the system would flag the gap.
Key takeaway: Transactional integrity answers whether one tenant's multi-step operation can end up half-finished. Tenant isolation answers whether one tenant can ever see another tenant's data. A platform needs both, and they are enforced independently.
How isolation holds across tenants
Sharing a data model across engines for a single tenant says nothing about how multiple tenants are separated from each other, and conflating the two is a reasonable source of confusion for a buyer evaluating "shared schema" risk. Infrakinetic isolates every tenant's data at the data layer, below the application, so isolation does not depend on every screen and every feature applying the correct filter by hand. Predictive scoring is trained and run separately per tenant, with no shared learning across customers. Writes to tenant-scoped tables are logged at the database layer independent of which API route made the change, so the audit trail does not rely on every code path remembering to log correctly.
The result is two separate guarantees held at once: one shared, atomic record per tenant across every engine that tenant uses, and complete isolation between tenants enforced below the point where an application bug could ever cross that line.