Greenplum Disaster Recovery: Full Data Protection for Big Data with a Modern Twist
Greenplum Disaster Recovery (GPDR), part of VMware Tanzu Greenplum, is a tool for replicating data to a secondary data center in case of disaster.? But what if we push its boundaries to be used in more use cases? Imagine full data protection to a second data center, read-only replicas for querying, and a fresh take on incremental backups and PITR—all orchestrated with GPDR. As of February 24, 2025, with Greenplum 7.3.4’s latest features, here are some innovative use cases to maximize data availability.
1. Continuous Read-Only Replicas in a Second Data Center
Why settle for a cold standby? GPDR’s continuous recovery workflow lets you sync a recovery cluster in a second data center with frequent restore points—think every 5-10 minutes. Instead of just waiting for disaster, promote this cluster as a read-only replica. By replaying WAL files over a full backup, you keep it nearly live with the primary site. Analysts can offload reporting queries here, reducing primary cluster load while ensuring data is always available across geographies. If disaster strikes, flip it to become the primary with minimal downtime.
2. Incremental Backup with Point In Time Recovery
Greenplum Disaster Recovery (GPDR) leverages Write-Ahead Log (WAL) archiving to capture all data modifications as they occur, storing them offline alongside full and incremental backup sets in a shared repository, such as NFS or S3. These archived WAL files, combined with backup data, enable GPDR to restore a Greenplum environment to any specific point in time covered by the backup set. A read-only replica can be established in a second data center and rolled back to a designated point, such as a previous quarter’s end, using the WAL replay process. Alternatively, the primary environment can be fully restored to a prior state by applying the archived WAL files to the backup, ensuring comprehensive data recovery.
How GPDR Works?
Greenplum Disaster Recovery (GPDR) provides a mechanism for data protection and recovery, relying on a combination of physical backups and Write-Ahead Log (WAL) archiving. The process starts with a full backup, which is a physical snapshot of the Greenplum database. Unlike logical backups that extract data through queries (potentially causing table locks or increased CPU usage), GPDR’s full backup copies the underlying database files directly from the filesystem. This includes data files, configuration files, and system metadata stored across all segments of the Greenplum cluster. By operating at the file level, the backup avoids imposing transactional locks or significant computational overhead, ensuring the primary database remains fully operational during the process.
Once the full backup establishes a baseline, GPDR continuously captures all subsequent modifications through WAL archiving. Every change—such as inserts, updates, or deletes—is recorded in WAL files before being applied to the database. These files are then archived to an offline storage location, such as NFS or S3, preserving a complete history of data changes. The combination of the physical full backup and archived WAL files allows GPDR to reconstruct the database state at any point in time within the backup’s scope. For recovery, GPDR restores the full backup to a target environment—such as a read-only replica in a second data center or the primary cluster—and replays the WAL files in sequence to reach the desired restore point. This approach ensures data consistency and availability without disrupting live operations during backup creation.
Conclusion
Greenplum users can enhance data safety and reliability by adopting Greenplum Disaster Recovery (GPDR). With its physical full backups and Write-Ahead Log archiving, GPDR ensures comprehensive data protection and flexible point-in-time recovery without impacting live operations. These features make it an effective solution for safeguarding critical workloads, enabling users to confidently deploy Greenplum for mission-critical applications where data availability and integrity are paramount.