## Sub-Second on the Lakehouse

# How Auraa Serves APIs from Databricks Without Breaking the Single Source of Truth

[Download the White Paper](/content/hubfs/resources/white-papers/Sub-Second-on-the-Lakehouse.pdf)

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

[Download the White Paper](/content/hubfs/resources/white-papers/Sub-Second-on-the-Lakehouse.pdf)

## Frequently Asked Questions

### Why is adding a second database a governance problem rather than a solution?

The moment a second database sits alongside Delta Lake, you have two sources of truth, two governance perimeters, and two audit trails. Any sync failure, schema change, or write that reaches one system but not the other fractures the integrity of both. The audit trail forks. Governance policies applied in Delta may not be applied in the secondary database. Auraa's foundational principle is that all platform metadata flows through the same Delta-backed medallion as business data -- and that principle cannot coexist with a second write authority.

### Why did Auraa retire Databricks Synced Tables after deploying across 35 governance tables?

Auraa deployed Databricks Synced Tables as a sub-second read layer across 35 governance tables in production. The whitepaper documents the exact failure modes encountered at that scale. The team retired Synced Tables and designed the GovernanceWriter pattern as a replacement. The whitepaper publishes the specific failure modes so that other teams can evaluate whether Synced Tables is appropriate for their workload without repeating the same discovery process.

### What is the GovernanceWriter pattern and how does it deliver sub-second reads?

The GovernanceWriter is a single application-layer component that writes to both Delta Lake and Lakebase in one coordinated operation. Delta receives the authoritative write first and remains the only write authority. Lakebase receives a synchronized read-optimized copy of the same governed state. API calls read from Lakebase at sub-second latency. If Lakebase state becomes inconsistent, the GovernanceWriter can rebuild it from the Delta audit trail. There is one write path, one governance perimeter, and one audit trail.

### What is the dual-surface read model and how does it avoid architectural compromise?

The dual-surface read model means the same governed state in Delta Lake powers two access patterns: analytical workloads via SQL Warehouse for batch processing and reporting, and live API calls via Lakebase for sub-second responses. Because both surfaces draw from the same governed state written by the GovernanceWriter, there is no architectural compromise: the data a SQL Warehouse query sees and the data an API call sees are the same data, governed by the same policies, captured in the same audit trail.

### What are the honest caveats of the GovernanceWriter approach?

The whitepaper identifies four caveats. Schema discipline: the Delta table and Lakebase must have compatible type systems, and schema changes must be applied to both in coordination. Type-system mapping: not all Delta types map cleanly to operational database types and translation decisions must be made explicitly. Connection pool management: the GovernanceWriter maintains connections to two systems and pool configuration becomes operationally significant at scale. Operating cost: the whitepaper publishes what this approach actually costs to run at Auraa's production scale.