Analytics in Hybrid Manager#
Welcome to the central resource for understanding and leveraging the analytics capabilities embedded within EDB Hybrid Manager (HM).
Hub quick links: Analytics Hub — Core Concepts — Related How-Tos
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 step: Configure an Iceberg 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.
Next step: Read Iceberg/Delta with or without a catalog
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 step: Tiered Tables in Hybrid Manager
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 step: 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:
Analytics concepts (hub) — Understand core patterns and capabilities.
Create a Lakehouse cluster — Deploy Lakehouse Clusters to enable scalable querying on object storage.
Configure an Iceberg catalog connection — Connect HM-managed or external catalogs to manage Iceberg tables.
Read with or without a catalog — Query Iceberg and Delta Lake tables from your Lakehouse Clusters.
Read/write without a catalog — Direct file-based access for development and testing.
Explore Persona-Based Guidance — Tailored recommendations for DBAs, DevOps/SREs, Data Scientists, and Developers.
Explore architectures and examples — Concepts and patterns to solve common analytics problems.
Analytics How-To Index — Step-by-step guides for configurations and operations.
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.
- Analytics Concepts in Hybrid Manager
- Delta Lake in Hybrid Manager
- Apache Iceberg in Hybrid Manager
- EDB Postgres Lakehouse Clusters on Hybrid Manager
- Tiered Tables in Hybrid Manager
- Why use Tiered Tables with Hybrid Manager
- Key terms and architecture overview
- When should I use Tiered Tables in Hybrid Manager?
- Use cases for Tiered Tables
- How Tiered Tables work in your HM architecture
- Prerequisites within EDB Hybrid Manager
- Main capabilities
- Getting started with Tiered Tables in Hybrid Manager
- Related resources
- Observability tips
- Next topic