Overview of Greenplum® and Apache Cloudberry™ DBMSs in Yandex MPP Analytics for PostgreSQL
Yandex MPP Analytics for PostgreSQL allows you to deploy analytical, column-oriented MPP database clusters based on PostgreSQL for large-scale data processing. Each DBMS aggregates multiple PostgreSQL databases into an MPP cluster and establishes communication between them via an Interconnect network. Each cluster node runs its own OS and uses dedicated memory and disk resources, enabling parallel data storage and processing across many nodes. This MPP architecture supports horizontal scaling, ensures high cluster availability, and delivers near-linear performance growth as you add resources.
The following databases are supported:
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Greenplum®: Based on PostgreSQL version 9.4.
Greenplum® was originally developed as an open-source project; however, in 2024, access to its source code was restricted. Despite this, Yandex MPP Analytics for PostgreSQL continues to support Greenplum® version 6 using its open-source fork.
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Apache Cloudberry™: Based on Greenplum® version 7 with a modernized PostgreSQL 14 kernel; supports dynamic tables and PAX format.
Apache Cloudberry™ is an open-source project developed under Apache License v2.0.
Apache Cloudberry™ will serve as the basis for future major versions of Yandex MPP Analytics for PostgreSQL.
Learn more about the differences between Apache Cloudberry™ and Greenplum® in this Apache Cloudberry™ guide.
Yandex MPP Analytics for PostgreSQL handles most of the cluster maintenance operations, including:
- Provisioning resources, creating and reconfiguring databases, and applying software updates.
- Automatically restoring cluster resilience after failures.
- Creating backups using WAL-G, storing them in an S3 storage, and enabling point-in-time recovery (PITR) to any moment.
The solution also provides self-service tools for managing clusters:
- Roles for data access management.
- Command center and metrics for real-time cluster monitoring.
- Yezzey extension for setting up hybrid storage.
Yandex MPP Analytics for PostgreSQL clusters support seamless integration with other Yandex Cloud services, e.g., with Yandex Data Transfer for database migration or Yandex DataLens for data visualization.
Yandex MPP Analytics for PostgreSQL use cases
- Analytical DB: For example, you can linearly accelerate large hash joins by adding more CPUs or nodes.
- General-purpose database replacement: Yandex MPP Analytics for PostgreSQL can be used as a drop-in alternative to Oracle DB, Microsoft SQL Server, or IBM DB2. It handles not only analytical workloads but also numerous short OLTP queries typical of PostgreSQL.
- High-performance alternative to PostgreSQL: Because databases available in Yandex MPP Analytics for PostgreSQL are based on PostgreSQL, it supports many familiar PostgreSQL tools, such as JDBC and ODBC drivers, and conforms to the ANSI SQL:2008 standard.
See also
- Official Greenplum® guides
- Official Apache Cloudberry™ guides
- Getting started with Yandex MPP Analytics for PostgreSQL
- Resource relationships in Yandex MPP Analytics for PostgreSQL
- Yandex MPP Analytics for PostgreSQL tutorials
Greenplum® and Greenplum Database® are registered trademarks or trademarks of Broadcom Inc. in the United States and/or other countries.
Apache® and Apache Cloudberry™ are registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.