Analytics/Lakehouse

Use the Analytics Accelerator to explore the analytical capabilities built on EDB Postgres®. This accelerator helps you understand core concepts, explore key technologies such as EDB Postgres® Lakehouse, and learn how to implement analytics with EDB Hybrid Manager (HM).

We integrate modern data architectures and open standards with the reliability and flexibility of Postgres to help you unlock valuable insights.

• Introduction
  • Navigating the analytics accelerator
  • Conceptual foundations
  • EDB core analytics technologies
  • Practical guidance and solutions
  • Product-specific implementations
  • Where to start
    • Level 100
    • Level 200
    • Level 300
• Quick start
  • Introduction
    • What to know
    • Basic architecture
  • Getting started
    • Create a Lakehouse node
  • Operating a Lakehouse node
    • Connect to the node
    • Understand the constraints
  • Inspect the benchmark datasets
  • Query the benchmark datasets
• Tiered Tables
  • What are Tiered Tables
  • Why Tiered Tables matter for EDB analytics
  • How EDB implements Tiered Tables
  • Common use cases
  • Role-based guidance
  • Learning paths
  • Related concepts
  • Next steps
• Reference - EDB Postgres® AI Lakehouse
  • Benchmarking datasets
  • Queries
  • Delta Lake Table tools
    • Creating Delta Lake Tables
  • DirectScan and fallback modes
    • DirectScan
    • Using EXPLAIN to check the query plan
  • User management
  • Loading data
    • Bringing your own data
  • PGAA functions reference
    • Synopsis
    • Parameters
    • Returns
    • Synopsis
    • Parameters
    • Returns
  • PGAA functions reference
    • pgaa.create_storage_location
  • Supported AWS instances
• Delta Lake
  • What is Delta Lake
  • Why Delta Lake matters for EDB analytics
  • How EDB leverages Delta Lake
  • Common use cases
  • Role-based guidance
  • Learning paths
  • Related concepts
  • Next steps
• Apache Iceberg
  • What is Apache Iceberg
    • Key goals
  • Key features and benefits
  • Why Apache Iceberg matters for EDB analytics
  • How EDB solutions implement Iceberg support
    • PGAA extensions
    • Catalog connectivity
    • Writing to Iceberg tables
  • Related topics
• EDB Postgres Lakehouse
  • What is the EDB Postgres Lakehouse
  • Why Lakehouse matters for EDB analytics
  • How EDB implements Lakehouse architecture
  • Common use cases
  • Role-based guidance
  • Learning paths
  • Related concepts
  • Next steps
• Analytics Accelerator learning resources
  • Documentation categories
    • Structured learning paths
    • Conceptual explanations
    • Tutorials
    • How-to guides
    • Use cases and solutions
    • Persona-based guidance
    • Analytics Accelerator in Hybrid Manager (HM)
• Analytics Accelerator learning resources
  • Analytics Accelerator concepts and technologies
  • Analytics Accelerator concepts and technologies
    • Foundational analytics and modern data architectures
  • Analytics Accelerator concepts and technologies
    • Deep dive into core Analytics Accelerator components
  • Analytics Accelerator concepts and technologies
    • Understanding analytics within EDB Hybrid Manager (HM)
    • AI/ML workloads and interoperability
  • Analytics Accelerator learning paths
    • How to use these learning paths
  • Analytics Accelerator learning paths
  • Analytics Accelerator learning paths
    • EDB training and certification
  • Analytics Accelerator learning paths
    • Next steps
  • a persona-based guide
    • Quickly find your role
    • Database administrator (DBA)
    • DevOps engineer / site reliability engineer (SRE)
    • Data scientist / data analyst
    • Application developer
  • Analytics Accelerator tutorials
    • Tutorial categories