Apache Cloudberry
by Apache Cloudberry · Open-source MPP data warehouse built on a PostgreSQL kernel
BenchRank score
Screenshots of Apache Cloudberry
Homepage
Overview
Apache Cloudberry is an open-source massively parallel processing (MPP) database derived from the open-source Greenplum Database and built on a PostgreSQL 14.4 kernel. It serves as a data warehouse for large-scale analytics and AI/ML workloads on commodity hardware, virtual machines or cloud. It includes parallel query execution, incremental materialized views, a hybrid PAX storage engine and transparent data encryption.
- Best for
- Teams running open-source Greenplum that want a vendor-neutral MPP warehouse for large-scale analytics
- Pricing
- No prices are shown; the project is described as 100% open source under the Apache License 2.0, with a download available from the site.
Strengths and trade-offs
Strengths
- Built on a PostgreSQL kernel with access to its extension ecosystem
- Migration path from open-source Greenplum using gpbackup
- Vendor-neutral, Apache-governed, Apache License 2.0
- PostGIS spatial analysis and Apache MADlib ML in one engine
Trade-offs
- Still an Apache incubator project, not yet fully endorsed by the ASF
- Self-hosted cluster; no managed or hosted service is mentioned
- Support is community-only: Slack, Discord, GitHub issues and discussions
- Greenplum compatibility is stated as a goal, so migrations need testing
How Apache Cloudberry markets itself
A structured read of the promise, proof and page design on Apache Cloudberry’s captured homepage.
Homepage capture
“Welcome to Apache Cloudberry™ (Incubating)”
- Angle: Open source / ownership
- Hero: Typography only
Pricing
Published plans and prices from Apache Cloudberry’s own pricing page.
How this score is made up
Each dimension is scored out of 100 and combined into the headline score using fixed weights.
MCP support
Whether an agent can drive the product through the Model Context Protocol, and how much setup that takes.
Documentation
Publicly reachable docs — coverage, freshness, code samples and machine readability.
Agent friendliness
How readable the site is to an automated client: llms.txt, structured data, server-rendered content, crawler access.
Changelog
A public, dated record of what shipped and when — the clearest signal that a product is still alive.
Marketing site structure
Whether the site answers a buyer's questions: clear positioning, the pages that matter, and accessibility.
Page speed
How fast the site loads for real visitors: Chrome UX Report 75th-percentile LCP, INP and CLS, with a Lighthouse mobile run standing in where a site has too little traffic for field data.
Operational trust
Status page and incident history, security disclosure, compliance and data-processing documentation.
Measured, but not part of the score
Useful to know, but not a mark for or against the product — so these do not affect the ranking.
Openness
Source availability, self-hosting, data export and open standards. Scored and shown, but not part of the composite — paid SaaS is not worse for being paid SaaS.
Maintenance
Release cadence and repository activity. Scored and shown, but not part of the composite — it is only measurable for open repositories.
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Where this comes from
The Apache Cloudberry pages BenchRank reads when it scores the product — its documentation, release notes, status and security pages, and its repository where there is one.
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