Reference Architectures

Validate architectures for enterprise AI workloads.

Three certified blueprints. Fourteen ecosystem partners. One open platform—in any environment you control.

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Validated Partners

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Blueprints

Three architectures. Every enterprise AI workload.

Each blueprint is a validated reference architecture combining EDB Postgres® AI with certified ecosystem partners—designed for a specific workload pattern, deployable in any environment you control.

Blueprint 01

Real-time ML inference at the data layer

Sub-second inference embedded in streaming data pipelines, eliminating external ML platform latency and governance gaps.

  • AI FACTORY
  • AGENTIC DATABASE
  • DISTRIBUTED HA

6 validated partners

View Blueprint 01

Blueprint 02

Unified search, analytics, and agentic reasoning

Vector, full-text, and SQL queries unified in a single platform—with agentic reasoning grounded in governed Postgres data.

  • AI FACTORY
  • AGENTIC DATABASE
  • CONVERGED ANALYTICS

6 validated partners

View Blueprint 02

Blueprint 03

Sovereign data lakehouse and regulatory analytics

Open Iceberg-native lakehouse with no vendor lock-in, purpose-built for regulatory-grade analytics across BFSI, healthcare, and telco.

  • WAREHOUSE ANALYTICS
  • SOVEREIGN DATA AND AI FACTORY
  • CERTIFIED HA

9 validated partners

View Blueprint 03

VALIDATED PARTNERS

14 validated integration partners.

Each partner has a validated integration with EDB Postgres AI and appears in one or more certified blueprints. Use the filter above to explore by category or blueprint.

Airflow (Astronomer)

Orchestrates the full lakehouse pipeline — ingestion, dbt transformation triggers, and WarehousePG analytical load — reliably at scale.
Transformation BP 01 BP 03
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Apache Iceberg

Extends EDB PG AI queries across data lake tables — open format, no duplication, no separate query engine required.
Storage BP 03
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dbt

Transforms source data natively in Postgres, aligned to BCBS 239, EBA ITS, OMOP CDM, with full lineage per run.
Transformation BP 01 BP 03
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Fivetran

Automated data pipelines into sovereign Postgres® AI infrastructure—zero custom ingestion code.
Data Integration BP 03
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Grafana

Monitors Airflow pipeline health, WarehousePG query performance, and lakehouse telemetry in a unified real-time view.
Visualization BP 01 BP 02 BP 03
View integration

Jupyter

Connects data scientists directly to governed WarehousePG and Iceberg data for population health and regulatory research.
Development BP 01 BP 03
View integration

Kafka / Redpanda

Streams high-velocity event data directly into EDB PG AI pipelines as queryable, transactional records — the ingest backbone for all three inference paths.
Streaming BP 01 BP 02
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KServe + NVIDIA NIM

Deploys GPU-optimized model endpoints that execute inference directly against live Postgres data — co-located, not external.
AI serving BP 01
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Lakekeeper (Vakamo)

Governs Iceberg table metadata across the lakehouse — unified access control, lineage, and discoverability for regulatory consumers.
Storage BP 01 BP 03
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Langflow

Orchestrates LLM reasoning pipelines over Analytics Engine retrieval results, using EDB PG AI as the agent runtime and state layer.
AI/ML BP 01
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Metabase

Surfaces compliance and analytical dashboards for regulatory and executive audiences — no data extraction required.
Visualization BP 02 BP 03
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MinIO

Provides sovereign S3-compatible object storage for Iceberg-formatted inference results, model artifacts, and long-term analytics data.
Storage BP 01 BP 02 BP 03
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MLflow

Tracks every model version, experiment, and deployment decision tied to EDB PG AI pipeline runs — full lineage from data to inference.
AI/ML BP 01
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RisingWave

Computes streaming materialized views in SQL, producing aggregated features for the ML inference layer in real time.
Streaming BP 01
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Tableau

Translates sovereign lakehouse data — BCBS 239-aligned regulatory outputs, clinical data — into governed executive visualizations.
Visualization BP 02 BP 03
View integration

Ready to build on a certified stack?

Explore the architecture documentation or talk directly with a solutions engineer about deploying a blueprint in your environment.

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