Building a FHIR-Native Health Data Platform on Databricks Lakebase
Your interoperability layer and your analytics platform, in one place.

The problem
Slow data
FHIR server here, warehouse there, ETL pipelines in between.
Split governance
Each system has its own access controls, audit trails, and compliance.
Stalled AI
Models can't reach clean, trusted data at the point of need.
One dataset, every tool, no data movement
Aidbox runs natively on Databricks Lakebase, a serverless Postgres inside the Data Intelligence Platform.
FHIR data standardized at entry
No transformation after the fact.
Immediately available everywhere
Spark, ML, AI agents, BI dashboards.
Zero data movement
No ETL, no copy, no delay.
How it works
Three steps to a unified FHIR-native data platform on Databricks.
Step 1. Aggregate and standardize
Health Samurai's open-source converters (HL7v2, C-CDA, X12) transform legacy data into FHIR. A terminology server normalizes codes across vocabularies. MDM/MPI deduplicates patients into a single golden record. Quality is enforced at the point of entry, not after the fact.
Step 2. Store on Lakebase, access everywhere
Aidbox runs on Lakebase. Data replicates through Moonlink with zero ETL, so operational FHIR data flows into the analytical layer without pipelines, without transformation, without delay. Two access patterns from a single dataset: Databricks-native (Spark, SQL, ML, AI/BI) and standards-based (FHIR API, SMART on FHIR, SQL on FHIR ViewDefinitions).
Step 3. Govern once with Unity Catalog
The same access controls, audit trails, and policies apply across both the clinical application layer and the analytics layer. No governance gaps. No reconciliation. One policy framework for all data.
Full platform architecture
Data Sources → Health Samurai Ingestion → Aidbox on Lakebase → dual access (FHIR + Databricks) → Use Cases, with Unity Catalog spanning everything and Moonlink as the zero-ETL bridge.
What you can build
A FHIR-native foundation unlocks three high-value use cases, without the usual data plumbing.
Clinical and administrative decision support powered by Databricks AI, connected back to EHR workflows through SMART on FHIR and CDS Hooks.
Build meaningful relationships with patients and members through standards-compliant infrastructure.
Build on FHIR and open standards, and CMS/ONC requirements are met by design.
Use cases
See what teams are already building, from clinical research to CMS compliance.
Aggregate data from multiple sources, validate it, and improve its quality on the way in. Everything is normalized to FHIR, so analytics runs on one clean dataset.
Why this matters now
Three forces are reshaping how healthcare data platforms are built.
CMS and ONC timelines won't wait for your ETL pipelines to catch up.
Models are moving from pilots to production, but only on trusted, standardized foundations.
FHIR + Lakebase + Unity Catalog means you own the architecture.
Platform at a glance
Eight building blocks that make up a FHIR-native health data platform on Databricks.
HL7v2, C-CDA, X12 converters (open-source).
FHIR-native server, cross-vocabulary normalization.
MDM/MPI: one golden record per patient.
Aidbox on Databricks Lakebase (serverless Postgres).
Moonlink replication to the analytical layer.
FHIR API, SMART on FHIR, SQL on FHIR ViewDefinitions, Spark, SQL, ML.
Unity Catalog across clinical + analytics layers.
FHIR R4 / R5 / R6, HL7 Implementation Guides.
Already running Aidbox outside Lakebase?
You don't need Lakebase to start. Aidbox can stream FHIR data into a Databricks lakehouse today through the AidboxTopicDestination subscription — no custom ETL pipelines required.
- Address
- Health Samurai Inc. 1891 N Gaffey St Ste O, San Pedro, CA 90731
- Telephone
- +1 (818) 731-1279
Get started
Health Samurai and Databricks: open technologies for your Health Data Platform.
