Most teams resolve this the wrong way: they add a second database alongside the lakehouse. And the moment they do, they've created two sources of truth, two governance perimeters, two audit trails, and the integrity they built is quietly fractured.
This whitepaper documents how Covasant's engineering team solved this.
Building Auraa, our agentic data platform natively on Databricks, we hit this wall head-on. Our foundational principle that all platform metadata flows through the same Delta-backed medallion as business data is what gives Auraa a single governance perimeter and a single audit trail. But Delta Lake, accessed through a SQL Warehouse, is not a sub-second point-read engine.
Download the White Paper to Learn:
- Why adding a second database is not a solution, it's the governance problem in disguise
- The exact failure modes that led us to retire Databricks Synced Tables after deploying it across 35 governance tables
- The Governance Writer pattern: how a single application-layer component delivers sub-second reads while keeping Delta as the only write authority
- The dual-surface read model: how the same governed state powers both analytical workloads and live API calls with no architectural compromise
- The honest caveats: schema discipline, type-system mapping, connection pool management, and what this approach actually costs to operate