This is a continuation of my posts on relational databases, started here. Previous posts on this theme, “Data Modeling“, “Let’s Talk About Database Schema“, “The Exasperating Topic of Database Indexes“, “The Keys & Relationships of Relational Databases“, “Relational Database Query Optimization“, “Normalization in Relational Databases“, “Database (DB) Caching and DB Tertiary Caching“, and “Security and Authentication in Relational Databases“.
In the realm of data management, ensuring the safety and recoverability of data is paramount. Relational databases, being at the core of many business operations, require robust backup and recovery strategies. This article delves into the general concepts of backup and recovery in relational databases, followed by specific strategies for SQL Server, Oracle, MariaDB/MySQL, and PostgreSQL.
General Concepts of Backup and Recovery in Relational Databases
Types of Backups
- Full Backup: Captures the entire database at a point in time.
- Incremental Backup: Records the changes since the last backup.
- Differential Backup: Stores data changed since the last full backup.
- Log Backup: Specific to databases that maintain transaction logs.
Recovery Models
- Simple Recovery Model: Ideal for scenarios where data recovery to a specific point in time is not critical.
- Full Recovery Model: Necessary for databases where data loss is unacceptable, allowing recovery to a specific point in time.
- Bulk-Logged Recovery Model: A variation of the full recovery model, optimizing for bulk operations.
Considerations for Backup and Recovery
- Recovery Point Objective (RPO): Determines how much data loss is acceptable.
- Recovery Time Objective (RTO): The acceptable time to restore operations after a failure.
- Storage Media: Choosing between on-site, off-site, or cloud storage.
- Encryption and Security: Ensuring data is protected during and after the backup process.
- Regular Testing: Regularly testing backups to ensure data integrity.
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