Analytics Evaluated
Greenplum logo

Greenplum

Greenplum is an open-source, massively parallel processing (MPP) data platform for analytics, machine learning, and AI. It is built on PostgreSQL and designed for large-scale data warehousing and advanced analytics workloads, allowing for high-performance querying and processing of petabytes of data.

Category / Domain Analytics
I/O Performance Empirical Profile

Core Information

#core_information

Name, description, vendor website, logo, technology type and tags.

Overview & Role

Greenplum is an open-source, massively parallel processing (MPP) data platform for analytics, machine learning, and AI. It is built on PostgreSQL and designed for large-scale data warehousing and advanced analytics workloads, allowing for high-performance querying and processing of petabytes of data.

Domain Classification & Tags

Performance Profile

#performance_profile

Typical read and write throughput, payload size and processing latency.

Read Performance Profile

Throughput: Varies widely, from 100s of MB/s to several GB/s per segment, aggregating to tens of GB/s for large clusters

Payload Size: Typically large, ranging from 100s of KB to several MB per row/record, or full table scans

Processing Latency: Sub-second for simple queries on indexed data, seconds to minutes for complex analytical queries on large datasets

Write Performance Profile

Throughput: Varies widely, from 10s of MB/s to 100s of MB/s per segment, aggregating to GB/s for large clusters during bulk loads

Payload Size: Typically large, ranging from 100s of KB to several MB per row/record, or bulk inserts/updates

Processing Latency: Seconds to minutes for large batch inserts/updates, sub-second for single row inserts (less common use case)

Architecture Diagram

#architecture_diagram

Reference diagram of the technology's internal architecture.

Component Architecture & Topology

open_in_new Standalone Tab

Features

#features

Catalogued product capabilities and what each one does.

Empirical data for features is currently being compiled in the global catalog.

Typical Use Cases

#typical_use_cases

Scenarios the technology is commonly chosen for.

Empirical data for typical use cases is currently being compiled in the global catalog.

Known Customers

#known_customers

Publicly referenced organisations using the technology.

Empirical data for known customers is currently being compiled in the global catalog.

Known Integrations

#known_integrations

Other products and services it is documented to work with.

Empirical data for known integrations is currently being compiled in the global catalog.

Connectors

#connectors

Directional data connections to other technologies, with direction and maturity.

Empirical data for connectors is currently being compiled in the global catalog.

Reference Architectures

#reference_architectures

Published architectures where the technology is used or mentioned.

No published reference architecture blueprints currently link to Greenplum.

Security Features

#security_features

Built-in security and access-control capabilities.

Empirical data for security features is currently being compiled in the global catalog.

Known Issues

#known_issues

Documented limitations, defects and operational pitfalls.

Empirical data for known issues is currently being compiled in the global catalog.

Guidelines

#guidelines

Recommended practices for adopting and operating the technology.

Empirical data for guidelines is currently being compiled in the global catalog.

Standards & Compliance

#standards_and_compliance

Standards, certifications and control requirements it maps to.

Empirical data for standards & compliance is currently being compiled in the global catalog.

Sources

#sources

Documentation and research references behind the recorded information.

Empirical data for sources is currently being compiled in the global catalog.

Expert Validation

#expert_validation

Whether domain experts reviewed and confirmed the content.

Empirical data for expert validation is currently being compiled in the global catalog.