{[project]} provides fast, reliable backup and restore for {[postgres]} and seamlessly scales to terabyte scale databases by implementing stream compression and parallel processing. https://github.com {[github-url-root]}/pgbackrest/pgbackrest {[github-url-base]}/blob/master {[github-url-base]}/issues {[github-url-base]}/archive/release {[github-url-master]}/LICENSE {[github-url-base]}/projects http://www.pgbackrest.org user-guide-index configuration command release http://www.crunchydata.com {[crunchy-url-base]}/crunchy-backup-manager http://www.resonate.com
Introduction

aims to be a reliable, easy-to-use backup and restore solution that can seamlessly scale up to the largest databases and workloads by utilizing algorithms that are optimized for database-specific requirements.

v{[version-stable]} is the current stable release. Release notes are on the Releases page.

Documentation for v1 can be found here. No further releases are planned for v1 because v2 is backward-compatible with v1 options and repositories.

Features
Parallel Backup & Restore

Compression is usually the bottleneck during backup operations but, even with now ubiquitous multi-core servers, most database backup solutions are still single-process. solves the compression bottleneck with parallel processing.

Utilizing multiple cores for compression makes it possible to achieve 1TB/hr raw throughput even on a 1Gb/s link. More cores and a larger pipe lead to even higher throughput.

Local or Remote Operation

A custom protocol allows to backup, restore, and archive locally or remotely via SSH with minimal configuration. An interface to query is also provided via the protocol layer so that remote access to is never required, which enhances security.

Multiple Repositories

Multiple repositories allow, for example, a local repository with minimal retention for fast restores and a remote repository with a longer retention for redundancy and access across the enterprise.

Full, Incremental, & Differential Backups

Full, differential, and incremental backups are supported. is not susceptible to the time resolution issues of rsync, making differential and incremental backups completely safe.

Backup Rotation & Archive Expiration

Retention polices can be set for full and differential backups to create coverage for any timeframe. WAL archive can be maintained for all backups or strictly for the most recent backups. In the latter case WAL required to make older backups consistent will be maintained in the archive.

Backup Integrity

Checksums are calculated for every file in the backup and rechecked during a restore. After a backup finishes copying files, it waits until every WAL segment required to make the backup consistent reaches the repository.

Backups in the repository are stored in the same format as a standard cluster (including tablespaces). If compression is disabled and hard links are enabled it is possible to snapshot a backup in the repository and bring up a cluster directly on the snapshot. This is advantageous for terabyte-scale databases that are time consuming to restore in the traditional way.

All operations utilize file and directory level fsync to ensure durability.

Page Checksums

has supported page-level checksums since 9.3. If page checksums are enabled will validate the checksums for every file that is copied during a backup. All page checksums are validated during a full backup and checksums in files that have changed are validated during differential and incremental backups.

Validation failures do not stop the backup process, but warnings with details of exactly which pages have failed validation are output to the console and file log.

This feature allows page-level corruption to be detected early, before backups that contain valid copies of the data have expired.

Backup Resume

An aborted backup can be resumed from the point where it was stopped. Files that were already copied are compared with the checksums in the manifest to ensure integrity. Since this operation can take place entirely on the backup server, it reduces load on the database server and saves time since checksum calculation is faster than compressing and retransmitting data.

Streaming Compression & Checksums

Compression and checksum calculations are performed in stream while files are being copied to the repository, whether the repository is located locally or remotely.

If the repository is on a backup server, compression is performed on the database server and files are transmitted in a compressed format and simply stored on the backup server. When compression is disabled a lower level of compression is utilized to make efficient use of available bandwidth while keeping CPU cost to a minimum.

Delta Restore

The manifest contains checksums for every file in the backup so that during a restore it is possible to use these checksums to speed processing enormously. On a delta restore any files not present in the backup are first removed and then checksums are taken for the remaining files. Files that match the backup are left in place and the rest of the files are restored as usual. Parallel processing can lead to a dramatic reduction in restore times.

Parallel, Asynchronous WAL Push & Get

Dedicated commands are included for pushing WAL to the archive and getting WAL from the archive. Both commands support parallelism to accelerate processing and run asynchronously to provide the fastest possible response time to .

WAL push automatically detects WAL segments that are pushed multiple times and de-duplicates when the segment is identical, otherwise an error is raised. Asynchronous WAL push allows transfer to be offloaded to another process which compresses WAL segments in parallel for maximum throughput. This can be a critical feature for databases with extremely high write volume.

Asynchronous WAL get maintains a local queue of WAL segments that are decompressed and ready for replay. This reduces the time needed to provide WAL to which maximizes replay speed. Higher-latency connections and storage (such as S3) benefit the most.

The push and get commands both ensure that the database and repository match by comparing versions and system identifiers. This virtually eliminates the possibility of misconfiguring the WAL archive location.

S3, Azure, and GCS Compatible Object Store Support

repositories can be located in S3, Azure, and GCS compatible object stores to allow for virtually unlimited capacity and retention.

Encryption

can encrypt the repository to secure backups wherever they are stored.

Compatibility with <postgres/> >= 8.3

includes support for versions down to 8.3, since older versions of PostgreSQL are still regularly utilized.

Getting Started

strives to be easy to configure and operate:

User guides for various operating systems and versions. Command reference for command-line operations. Configuration reference for creating configurations.
Contributions

Contributions to are always welcome! Code fixes or new features can be submitted via pull requests. Ideas for new features and improvements to existing functionality or documentation can be submitted as issues. You may want to check the Project Boards to see if your suggestion has already been submitted. Bug reports should be submitted as issues. Please provide as much information as possible to aid in determining the cause of the problem. You will always receive credit in the release notes for your contributions.

Support

is completely free and open source under the MIT license. You may use it for personal or commercial purposes without any restrictions whatsoever. Bug reports are taken very seriously and will be addressed as quickly as possible. Creating a robust disaster recovery policy with proper replication and backup strategies can be a very complex and daunting task. You may find that you need help during the architecture phase and ongoing support to ensure that your enterprise continues running smoothly. Crunchy Data provides packaged versions of for major operating systems and expert full life-cycle commercial support for and all things . Crunchy Data is committed to providing open source solutions with no vendor lock-in, ensuring that cross-compatibility with the community version of is always strictly maintained. Please visit Crunchy Data for more information.

Recognition

Primary recognition goes to Stephen Frost for all his valuable advice and criticism during the development of . Crunchy Data has contributed significant time and resources to and continues to actively support development. Resonate also contributed to the development of and allowed early (but well tested) versions to be installed as their primary backup solution.

Armchair graphic by Sandor Szabo.