Analytics in Hybrid Manager

Analytics in Hybrid Manager#

Welcome to the central resource for understanding and leveraging the analytics capabilities embedded within EDB Hybrid Manager (HM).

Hybrid Manager provides integrated support for:

  • Apache Iceberg and catalog services

  • Delta Lake querying

  • Tiered Tables with EDB Postgres Distributed (PGD)

  • Lakehouse Clusters for high-speed analytics on object storage

  • Unified management and observability of your analytics stack

By using these capabilities, you can build modern, cost-effective analytics architectures on Postgres with reduced operational overhead—fully managed through Hybrid Manager.

Why Analytics in Hybrid Manager#

EDB Hybrid Manager integrates analytics to help you:

  • Gain unified visibility: View key metrics and operational trends across your entire EDB Postgres fleet managed by HM.

  • Optimize performance: Identify performance bottlenecks and understand query behavior within HM-managed databases and Lakehouse Clusters.

  • Manage resources efficiently: Monitor and tune resource consumption for HM-managed instances, including analytical workloads.

  • Enhance operational health: Track the availability and status of analytical components and underlying database infrastructure.

  • Simplify data architectures: Provision and manage EDB Postgres Lakehouse Clusters, implement Tiered Tables with PGD, and integrate with object storage—all from HM.

Core Concepts and Capabilities#

Apache Iceberg#

In Hybrid Manager, Iceberg is used to:

  • Manage large analytical tables in Iceberg format, queried by Lakehouse Clusters.

  • Support PGD offloading of cold partitions to object storage in Iceberg format.

  • Enable interoperability with external tools (Spark, Trino, etc.) via catalog-managed tables.

  • Facilitate catalog management via HM-managed services (Lakekeeper) or external catalogs.

Apache Iceberg in Hybrid Manager

Next topic: Configure an Iceberg REST catalog connection

Delta Lake#

Hybrid Manager supports querying Delta Lake tables:

  • Lakehouse Clusters can query existing Delta Lake tables stored in object storage.

  • Integrate HM-managed Lakehouse with Delta-based pipelines (Spark, Databricks, etc.).

  • Enable fast analytics on existing Delta data lakes via Lakehouse Clusters.

Delta Lake in Hybrid Manager

Next topic: Query Delta Lake tables

Tiered Tables with PGD#

Tiered Tables enable efficient management of large time-series datasets:

  • PGD’s AutoPartition automates time-based partitioning.

  • Cold partitions are offloaded to Iceberg format in object storage.

  • Lakehouse Clusters provide query access across hot and cold data.

  • Hybrid Manager helps configure and monitor Tiered Tables end-to-end.

Tiered Tables in Hybrid Manager

Next topic: Configure BDR AutoPartition with analytics offload

Lakehouse Clusters#

Lakehouse Clusters are managed compute nodes in HM:

  • Provide scalable, vectorized query execution on object storage.

  • Support both Iceberg and Delta Lake formats.

  • Integrate with catalogs (HM-managed or external).

  • Unified with the broader HM ecosystem (PGD offloading, Tiered Tables, BI integrations).

EDB Postgres Lakehouse Clusters on Hybrid Manager

Next topic: Create a Lakehouse cluster

How These Capabilities Work Together#

  • Data offloading: PGD clusters offload cold data to object storage in Iceberg format.

  • Catalog services: HM integrates with catalogs to manage table metadata; Lakehouse and PGD query through these catalogs.

  • Lakehouse Clusters: Managed compute nodes run scalable analytical queries on offloaded data.

  • Delta Lake integration: Lakehouse Clusters also query existing Delta Lake tables in place.

  • Unified management: Hybrid Manager provides a single control plane to provision, configure, monitor, and optimize your analytics architecture.

Getting Started: Quickstart Checklist#

Follow this checklist to begin applying Hybrid Manager analytics features:

Explore Further#

By leveraging these capabilities, Hybrid Manager enables you to build a modern, flexible, and performant analytics architecture across your EDB Postgres deployments—all through a unified and operationally efficient experience.

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