Massively Parallel Postgres for Analytics



Experience Greenplum Database, an open-source massively parallel data platform for analytics, machine learning and AI 

Power at scale

High performance on petabyte-scale data volumes

With its unique cost-based query optimizer designed for large-scale data workloads, Greenplum scales interactive and batch-mode analytics to large datasets in the petabytes without degrading query performance and throughput.

Greenplum is fully equipped with the analytical tools necessary to help you draw additional insights from your data. 

True Flexibility

Deploy anywhere

Based on PostgreSQL, Greenplum provides you with more control over the software you deploy, reducing vendor lock-in, and allowing open influence on product direction.

Take advantage of the flexibility and choice as Greenplum can be deployed on all major public and private cloud platforms,  on-premises, and on containerized infrastructure.

All the reasons to choose Greenplum

Fully featured, integrated analytics platform

MPP Architecture

Greenplum’s massively parallel processing architecture provides automatic parallelization of all data and queries in a scale-out, shared nothing architecture.

Petabyte-Scale Loading

High-performance loading uses MPP technology. Loading speeds scale with each additional node to greater than 10 terabytes per hour, per rack.

Innovative Query Optimization

The query optimizer available in Greenplum Database is the industry’s first cost-based query optimizer for big data workloads. It can scale interactive and batch mode analytics to large datasets in the petabytes without degrading query performance and throughput.

Polymorphic Data Storage

Fully control the configuration for your table and partition storage, execution, and compression. Design your tables based on the way data is accessed. Users have the choice of row or column-oriented storage and processing for any table or partition.

Integrated In-Database Analytics

Provided by Apache MADlib, a library for scalable in-database analytics extending the SQL capabilities of Greenplum Database through user-defined functions.

Federated Data Access

Query external data sources with the Greenplum optimizer and query processing engine. Including Hadoop, Cloud Storage, ORC, AVRO, Parquet and other Polyglot data stores.

Latest Events

Attend the latest Greenplum talks, meetups, and conferences

Platform Extension Framework (PXF): Enabling Parallel Query Processing Over Heterogeneous Data Sources In Greenplum

Authors: Venkatesh Raghavan, Alexander Denissov, Francisco Guerrero, Oliver Albertini, Divya Bhargov, Lisa Owen, Shivram Mani, Lav Jain Abstract: With the explosion of data stores and cloud services, data now resides[…]

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Image Classification in Greenplum Database Using Deep Learning

Authors: Oliver Albertini, Divya Bhargov, Alexander Denissov, Francisco Guerrero, Nandish Jayaram, Nikhil Kak, Ekta Khanna, Orhan Kislal, Arun Kumar, Frank McQuillan, Lisa Owen, Venkatesh Raghavan, Domino Valdano, Yuhao Zhang Abstract:[…]

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Bottom-up Join Enumeration in a Top-down Optimizer

Authors: Bhuvnesh Chaudhary, Hans Zeller, Sambitesh Dash, Venkatesh Raghavan MAPBU, VMWare Palo Alto CA, USA Abstract: Greenplum Database is a massively parallel processing (MPP) analytics database that adopts a shared-nothing[…]

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