Blueprint 3 · Sovereign Data Lakehouse
Sovereign data lakehouse on open standards. No cloud lock-in, no proprietary formats.
Regulatory-grade analytics on infrastructure you control, using Apache Iceberg on object storage you own.
On-premises, air-gapped, or any cloud—open formats throughout
Built-in, point-in-time query auditing via Iceberg snapshots—no additional tooling
Analytics Engine queries Iceberg directly through Lakekeeper—no data copy to a separate warehouse
How it's built
How it works
Architecture flow
| 01 | INTEGRATE | Source data ingests from operational EDB Postgres® AI (EDB PG AI) systems and external data sources via Fivetran, orchestrated by Airflow/Astronomer on a governed pipeline schedule. |
| 02 | TRANSFORM | dbt runs SQL-first transformation logic natively against Postgres, aligning source data to regulatory and compliance schemas—examples such as BCBS 239, EBA ITS, or OMOP CDM—with full lineage and testability per run. |
| 03 | CATALOG | Lakekeeper (Vakamo) governs Iceberg table metadata across the entire lakehouse layer—unified access control, lineage tracking, and discoverability for all downstream consumers. |
| 04 | STORE | Data lands in open Apache Iceberg format on MinIO object storage, fully on-premises with encryption at rest. Iceberg's versioned snapshot model enables point-in-time auditing without additional tooling. No cloud dependency, no proprietary format, no vendor lock-in. |
| 05 | ANALYZE | The Analytics Engine (PGAA) executes complex regulatory and analytical queries against Iceberg tables through the Lakekeeper catalog, with columnar acceleration over Parquet. |
| 06 | REPORT | Metabase and Tableau surface regulatory outputs, population health analytics, and supply chain intelligence through governed Postgres interfaces to analysts, executives, and compliance teams. PGAA and ClickHouse help provide high-performance query for reporting. |
Blueprint 3 · PARTNER STACK
Certified partners in this blueprint
Airflow (Astronomer)
Apache Iceberg
dbt
Fivetran
Grafana
Jupyter
Lakekeeper (Vakamo)
Metabase
MinIO
Tableau
INDUSTRY USE CASES
Blueprint 3 in production
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BFSIBFSI
Regulatory reporting and Basel III/IV compliance
A G-SIB producing 200+ regulatory reports across 30 jurisdictions runs $50M+ annual regulatory technology spend across 12 legacy warehouses with inconsistent data definitions. Consolidating regulatory data into a sovereign Iceberg lakehouse—with dbt managing BCBS 239-aligned transformations and Lakekeeper providing lineage—eliminates the fragmentation that drives restatements and audit failures. All data remains in jurisdiction-specific deployments.
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HealthcareHealthcare
Clinical data warehouse and population health analytics
A large health system spanning 50 hospitals across 8 different EHR systems cannot perform longitudinal patient analysis at the enterprise level. Deploying WarehousePG as the clinical data warehouse with OMOP CDM schema managed by dbt—with PHI stored in on-premises MinIO—enables cross-system patient matching and population health queries that were previously impossible within regulatory constraints.
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TelcoTelco
CDR analytics and lawful intercept compliance
A national carrier retains 7 years of Call Detail Records for regulatory compliance across a costly, slow Hadoop-based archive. Migrating the CDR archive to Iceberg tables on MinIO with the Analytics Engine (PGAA) as the query engine delivers a sovereign, queryable archive with dramatically reduced operational overhead.
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ManufacturingManufacturing
Supply chain traceability and ESG reporting
An automotive OEM must demonstrate full supply chain traceability for battery materials and maintain 15-year warranty data retention. A unified lakehouse connecting supplier data, production MES, quality systems, and field service data enables full genealogy queries across the product lifecycle. Iceberg time-travel provides point-in-time auditing for regulatory inquiries.
Validated deployment environments
Sovereign by design: runs fully on-premises, in any cloud, or across hybrid environments — open formats throughout.
Build your sovereign data lakehouse on open standards.
Run regulatory and analytical workloads on infrastructure you control, using formats you own. Talk to a solutions engineer or explore the architecture documentation.