Recovery Techniques in DBMS

Introduction

In any Database Management System (DBMS), data recovery is an essential component. Data recovery mechanisms in DBMS ensure that the database remains consistent and correct even in the face of failures like system crashes, database corruption, or user errors. 

This article explores several key recovery techniques in DBMS and provides a foundational understanding of their operations.

Types of Recovery Techniques in DBMS

A transaction is a unit of work in ACID properties: Atomicity, Consistency, Isolation, Durability. DBMS recovery maintains these properties, restoring the database to the last consistent state post-failure. 

Backup and Restoration

The most basic recovery technique is the regular backup of the database. DBAs can schedule backups to run periodically, storing snapshots of the database. In the event of a failure, the latest backup is restored.

For instance, in SQL Server, you can backup your database using the following SQL command:

BACKUP DATABASE YourDB
TO DISK = 'C:\backups\YourDB.bak';

And restore it using:

RESTORE DATABASE YourDB
FROM DISK = 'C:\backups\YourDB.bak';

Log-Based Recovery

The log-based recovery technique uses logs, or history lists, of each transaction. Each transaction log includes the transaction identifier, the data item affected, the type of operation, and the before and after values of the update.

In case of a system failure, the system checks the logs and undoes any transaction that was not completed before the failure, ensuring the Atomicity and Consistency of the database.

Also See, joins in dbms

Checkpoints

Checkpoints are points of synchronization between the database and the transaction log. At a checkpoint, all buffers are written to disk, and a special checkpoint record is added to the transaction log. In case of failure, recovery starts from the last checkpoint, reducing recovery time and effort.

Shadow Paging

Shadow paging is a technique suitable for databases stored on disk. It involves maintaining a shadow directory, or a copy of the database. When a transaction begins, the DBMS points to the shadow database. Any changes are reflected in a new copy of the database, preserving the shadow copy. In case of failure, the DBMS reverts to the shadow copy, maintaining database consistency.

Also read - multiple granularity in dbms, Entity in DBMS and What is schema in dbms

Database Replication

Database replication involves copying and maintaining the same set of data across multiple databases. This ensures redundancy, improves availability, and can enhance performance by distributing workload.

Point-in-Time Recovery

Point-in-Time Recovery (PITR) allows restoring a database to a specific moment in time, rather than just the latest backup. It involves using transaction logs to roll forward or backward to the desired timestamp, enabling recovery to a precise state before data loss or corruption.