Analytics Concepts in Hybrid Manager v1.3

Hybrid Manager enables you to build modern data lakehouse and analytics solutions for EDB Postgres.

Hub quick links: Analytics Hub — Concepts — How-Tos

This page introduces key concepts as they are applied in Hybrid Manager — with links to detailed explanations in the Analytics Hub for background.

Architecture overview

Hybrid Manager integrates the following layers:

• Lakehouse Clusters for scalable analytical compute
• Object Storage for cost-efficient analytical data storage
• PGD Clusters for transactional workloads and automated Tiered Tables offload
• Catalog Services (HM-managed or external) for metadata and interoperability
• PGAA and PGFS to bridge Postgres with the data lake

This architecture enables both Postgres-first and multi-engine data lakehouse designs.

For a general introduction, see What is a Postgres Lakehouse.

Lakehouse Clusters in Hybrid Manager

Lakehouse Clusters provide scalable analytical compute in Hybrid Manager:

• Provisioned and managed through HM
• Equipped with PGAA extensions for vectorized query execution
• Designed to query data in object storage (Iceberg, Delta Lake)
• Interoperable with external tools (Spark, Trino)

Lakehouse Clusters are central to analytics in Hybrid Manager.

Learn more: EDB Postgres Lakehouse: An Overview

Apache Iceberg in Hybrid Manager

Hybrid Manager integrates Iceberg as the primary table format for offloaded and analytical data:

• PGD clusters offload data to Iceberg format for Tiered Tables
• Lakehouse Clusters query Iceberg tables efficiently
• Catalog services (Lakekeeper or external) manage Iceberg table metadata

Iceberg provides an open and reliable foundation for lakehouse architectures in HM.

Conceptual overview: Apache Iceberg with EDB Solutions

Delta Lake in Hybrid Manager

Delta Lake provides additional flexibility:

• Lakehouse Clusters can query existing Delta Lake tables in object storage
• Common in environments with Spark/Databricks pipelines
• Delta Lake support in HM is currently read-only

Hybrid Manager enables Postgres-based analytics on Delta Lake data without ETL.

Conceptual overview: Understanding Delta Lake with EDB Solutions

Tiered Tables in Hybrid Manager

Tiered Tables provide automated lifecycle management of large time-series or historical datasets:

• PGD clusters use BDR AutoPartition to manage partitions
• Older partitions are offloaded automatically to object storage in Iceberg format
• Lakehouse Clusters and PGD parent tables can query both hot and cold data

Tiered Tables are a key optimization pattern for combining transactional and analytical workloads in Hybrid Manager.

Conceptual overview: Understanding Tiered Tables with EDB Postgres

PGAA and PGFS in Hybrid Manager

PGAA (Analytics Accelerator)

PGAA extensions provide:

• Vectorized query execution
• Integration with object storage via PGFS
• Support for querying Iceberg and Delta Lake tables
• Catalog integration

PGAA powers both Lakehouse Clusters and PGD offload pipelines.

PGFS (Postgres File System)

PGFS defines object storage locations:

• Used by PGAA to read/write data in object storage
• Supports S3-compatible storage, GCS, and others
• Configured in both PGD clusters and Lakehouse Clusters

PGFS is a simple but critical building block for data lake integration.

How these concepts fit together in Hybrid Manager

Next topic

Solving Analytics Problems in Hybrid Manager