Cloud data warehouses · Greenplum open-source community (originally Pivotal/VMware)

Greenplum

Open-source, massively parallel PostgreSQL-based data warehouse for large-scale analytical SQL.

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Greenplum is an open-source, massively parallel processing (MPP) data warehouse built on top of PostgreSQL. It shards tables across a cluster of PostgreSQL segment instances coordinated by a master node, giving it PostgreSQL's SQL surface and extensibility with horizontally scaled query execution for large analytical workloads. It supports column- and row-oriented storage, in-database machine learning through the MADlib library, and geospatial and text analytics via PostgreSQL extensions such as PostGIS. Greenplum is self-hosted: it runs on-premises or on virtual machines/Kubernetes across any cloud, with no vendor-managed SaaS offering maintained by the core project today. It suits organizations that want an open-source alternative to commercial MPP warehouses and are comfortable operating the cluster themselves.

At a glance

Vendor Greenplum open-source community (originally Pivotal/VMware)
Pricing model Open source + paid options
Free tier Yes
Deployment Self-hosted
Open source Yes (Apache-2.0)
Best for Organizations wanting a self-managed, open-source MPP warehouse with PostgreSQL compatibility.

Pricing

Free and open source under the Apache 2.0 license; no vendor-hosted SaaS tier, so costs are limited to the infrastructure it runs on.

Pricing has not been verified yet — see the vendor's site.

Features

  • Massively parallel processing built on PostgreSQL
  • Column- and row-oriented table storage options
  • In-database machine learning via MADlib
  • PostGIS-based geospatial analytics
  • Resource groups for workload management and query prioritization
  • External tables for querying data in S3-compatible object storage
  • Standard PostgreSQL drivers, extensions, and SQL compatibility

Integrations

Profile last reviewed September 21, 2026

Alternatives

OpenText Vertica Columnar MPP analytics database, now owned by OpenText, deployable on-premises, in Kubernetes, or across major clouds. Exasol In-memory, massively parallel analytics database available as a managed cloud service or self-hosted software. Teradata VantageCloud Teradata's cloud-delivered evolution of its enterprise MPP data warehouse, unified under a single Teradata Unit pricing currency.

Greenplum in the index now

Terms to know

Data warehouse A centralized, structured database optimized for fast historical reporting rather than day-to-day transactions. OLAP (online analytical processing) A category of technology optimized for fast, multi-dimensional aggregation and slicing of data for analysis. Machine learning Building models that learn patterns from data to make predictions or decisions, rather than following hand-coded rules. Massively parallel processing An architecture that splits a query across many independent compute nodes, each processing its own data slice. Text analytics The techniques used to extract structured information and insight from unstructured text, from keyword counts to deep NLP.

Related guides

How to choose a cloud data warehouse Start from your cloud, your pricing tolerance and your workload shape — general BI, high-concurrency apps, or enterprise mixed workloads — not the feature list.