EDB Postgres AI analytics

The EDB Postgres AI analytics products extend Postgres with high-performance analytical capabilities, from vectorized query execution over open table formats in object storage to massively parallel processing (MPP) for large-scale data warehousing workloads.

Postgres Analytics Accelerator (PGAA)

Postgres Analytics Accelerator (PGAA) is a high-performance Postgres extension that enables querying large-scale data stored in open table formats like Delta Lake, Apache Iceberg, and Parquet directly from Postgres.

By offloading heavy analytical queries to a vectorized execution engine, PGAA bridges the gap between operational databases and data lakes without requiring data movement.

Key capabilities:

• Read tables in object storage: Query Parquet, Delta Lake, and Iceberg files in S3, GCS, or Azure using standard SQL.
• Iceberg catalog integration: Connect to external Iceberg REST catalogs to manage table metadata.
• Write to object storage: Write Postgres data out to optimized lakehouse formats in your object store using CTAS.
• Spark acceleration: Offload massive datasets and complex joins to a remote Spark cluster, with optional GPU acceleration via NVIDIA RAPIDS.
• Replicate with PGD: Combine with EDB Postgres Distributed for automated partition offloading and real-time replication.

WarehousePG

WarehousePG is an open-source massively parallel processing (MPP) database built on Postgres, designed for large-scale analytical and data warehousing workloads.

Key capabilities:

• Massively parallel processing: Distribute query execution across multiple segments for high-throughput analytical queries.
• Support for Greenplum migrations: Tools and guidance for migrating existing Greenplum workloads to WarehousePG.
• WarehousePG Enterprise Manager (WEM): Monitor, manage, and optimize your WarehousePG cluster.
• FlowServer: High-speed data loading into WarehousePG.
• whpg-copy: A utility for efficient bulk data copy operations.