Learn why Massively Parallel Postgres (MPP) platforms like Greenplum, WarehousePG, and Cloudberry need both logical backups and modern Point-In-Time Recovery to meet real DR requirements. This blog from guest blogger Greg Spiegelberg explains how these data protection techniques all fit and complement each other.

From script sprawl to structured, drill-down diagnostics.

When I assess customer Greenplum environments, I lean on a suite of lightweight shell utilities that make deep inspection fast and repeatable. At the core is gpview.sh, an interactive catalog viewer. Around it are wrappers for scheduled health checks, single-report runs, and persistence for trending over time.

Disaster Recovery (DR) isn’t just “take a backup.” At MPP scale, you need a repeatable end-to-end flow with minimal coordination and downtime. This post walks through the DBA Operations Kickstarter framework that wraps gpbackup, gpbackup_manager, and gprestore into a fully automated DR pipeline

Partitioning is a cornerstone of scalable analytics in Greenplum Database. The hardest part of partitioning isn’t design, it’s keeping partitions current. The kickstarter Partition Maintenance toolset is a set of Bash/Python utilities that operationalizes this lifecycle for Greenplum. This post will dive into this set of tools.

We understand the challenges of provisioning and operationalizing a Greenplum or Cloudberry data warehouse environment. Whether you’re deploying on physical infrastructure, virtual platforms, or the cloud, setting up a high-performance MPP database requires precision, expertise, and automation.

The DBA Operations Kickstarter is a comprehensive toolkit designed by Mugnano Data Consulting to automate and operationalize best-practice DBA workflows for Greenplum and Cloudberry environments. Whether you're onboarding a new system or stabilizing an existing one, this solution delivers an enterprise-grade operational foundation in hours, not months.