
- DBMS - Home
- DBMS - Overview
- DBMS - Architecture
- DBMS - Data Models
- DBMS - Data Schemas
- DBMS - Data Independence
- DBMS - System Environment
- Centralized and Client/Server Architecture
- DBMS - Classification
- Relational Model
- DBMS - Codd's Rules
- DBMS - Relational Data Model
- DBMS - Relational Model Constraints
- DBMS - Relational Database Schemas
- DBMS - Handling Constraint Violations
- Entity Relationship Model
- DBMS - ER Model Basic Concepts
- DBMS - ER Diagram Representation
- Relationship Types and Relationship Sets
- DBMS - Weak Entity Types
- DBMS - Generalization, Aggregation
- DBMS - Drawing an ER Diagram
- DBMS - Enhanced ER Model
- Subclass, Superclass and Inheritance in EER
- Specialization and Generalization in Extended ER Model
- Data Abstraction and Knowledge Representation
- Relational Algebra
- DBMS - Relational Algebra
- Unary Relational Operation
- Set Theory Operations
- DBMS - Database Joins
- DBMS - Division Operation
- DBMS - ER to Relational Model
- Examples of Query in Relational Algebra
- Relational Calculus
- Tuple Relational Calculus
- Domain Relational Calculus
- Relational Database Design
- DBMS - Functional Dependency
- DBMS - Inference Rules
- DBMS - Minimal Cover
- Equivalence of Functional Dependency
- Finding Attribute Closure and Candidate Keys
- Relational Database Design
- DBMS - Keys
- Super keys and candidate keys
- DBMS - Foreign Key
- Finding Candidate Keys
- Normalization in Database Designing
- Database Normalization
- First Normal Form
- Second Normal Form
- Third Normal Form
- Boyce Codd Normal Form
- Difference Between 4NF and 5NF
- Structured Query Language
- Types of Languages in SQL
- Querying in SQL
- CRUD Operations in SQL
- Aggregation Function in SQL
- Join and Subquery in SQL
- Views in SQL
- Trigger and Schema Modification
- Storage and File Structure
- DBMS - Storage System
- DBMS - File Structure
- DBMS - Secondary Storage Devices
- DBMS - Buffer and Disk Blocks
- DBMS - Placing File Records on Disk
- DBMS - Ordered and Unordered Records
- Indexing and Hashing
- DBMS - Indexing
- DBMS - Single-Level Ordered Indexing
- DBMS - Multi-level Indexing
- Dynamic B- Tree and B+ Tree
- DBMS - Hashing
- Transaction and Concurrency
- DBMS - Transaction
- DBMS - Concurrency Control
- DBMS - Deadlock
- Backup and Recovery
- DBMS - Data Backup
- DBMS - Data Recovery
- DBMS Useful Resources
- DBMS - Quick Guide
- DBMS - Useful Resources
- DBMS - Discussion
DBMS - Data Backup
Loss of Volatile Storage
A volatile storage like RAM stores all the active logs, disk buffers, and related data. In addition, it stores all the transactions that are being currently executed. What happens if such a volatile storage crashes abruptly? It would obviously take away all the logs and active copies of the database. It makes recovery almost impossible, as everything that is required to recover the data is lost.
Following techniques may be adopted in case of loss of volatile storage −
We can have checkpoints at multiple stages so as to save the contents of the database periodically.
A state of active database in the volatile memory can be periodically dumped onto a stable storage, which may also contain logs and active transactions and buffer blocks.
<dump> can be marked on a log file, whenever the database contents are dumped from a non-volatile memory to a stable one.
Recovery
When the system recovers from a failure, it can restore the latest dump.
It can maintain a redo-list and an undo-list as checkpoints.
It can recover the system by consulting undo-redo lists to restore the state of all transactions up to the last checkpoint.
Database Backup & Recovery from Catastrophic Failure
A catastrophic failure is one where a stable, secondary storage device gets corrupt. With the storage device, all the valuable data that is stored inside is lost. We have two different strategies to recover data from such a catastrophic failure −
Remote backup &minu; Here a backup copy of the database is stored at a remote location from where it can be restored in case of a catastrophe.
Alternatively, database backups can be taken on magnetic tapes and stored at a safer place. This backup can later be transferred onto a freshly installed database to bring it to the point of backup.
Grown-up databases are too bulky to be frequently backed up. In such cases, we have techniques where we can restore a database just by looking at its logs. So, all that we need to do here is to take a backup of all the logs at frequent intervals of time. The database can be backed up once a week, and the logs being very small can be backed up every day or as frequently as possible.
Remote Backup
Remote backup provides a sense of security in case the primary location where the database is located gets destroyed. Remote backup can be offline or real-time or online. In case it is offline, it is maintained manually.

Online backup systems are more real-time and lifesavers for database administrators and investors. An online backup system is a mechanism where every bit of the real-time data is backed up simultaneously at two distant places. One of them is directly connected to the system and the other one is kept at a remote place as backup.
As soon as the primary database storage fails, the backup system senses the failure and switches the user system to the remote storage. Sometimes this is so instant that the users cant even realize a failure.