Skip to content
geeksforgeeks
  • Tutorials
    • Python
    • Java
    • Data Structures & Algorithms
    • ML & Data Science
    • Interview Corner
    • Programming Languages
    • Web Development
    • CS Subjects
    • DevOps And Linux
    • School Learning
    • Practice Coding Problems
  • Courses
    • DSA to Development
    • Get IBM Certification
    • Newly Launched!
      • Master Django Framework
      • Become AWS Certified
    • For Working Professionals
      • Interview 101: DSA & System Design
      • Data Science Training Program
      • JAVA Backend Development (Live)
      • DevOps Engineering (LIVE)
      • Data Structures & Algorithms in Python
    • For Students
      • Placement Preparation Course
      • Data Science (Live)
      • Data Structure & Algorithm-Self Paced (C++/JAVA)
      • Master Competitive Programming (Live)
      • Full Stack Development with React & Node JS (Live)
    • Full Stack Development
    • Data Science Program
    • All Courses
  • Aptitude
  • Engineering Mathematics
  • Discrete Mathematics
  • Operating System
  • DBMS
  • Computer Networks
  • Digital Logic and Design
  • C Programming
  • Data Structures
  • Algorithms
  • Theory of Computation
  • Compiler Design
  • Computer Org and Architecture
Open In App
Next Article:
Implementation of Locking in DBMS
Next article icon

Recoverability in DBMS

Last Updated : 25 Jun, 2025
Comments
Improve
Suggest changes
Like Article
Like
Report

Recoverability is a critical feature of database systems. It ensures that after a failure, the database returns to a consistent state by permanently saving committed transactions and rolling back uncommitted ones. It relies on transaction logs to undo or redo changes as needed. This is crucial in multi-transaction environments to prevent cascading failures and maintain data integrity and consistency.

There are several levels of recoverability that can be supported by a database system:

  • No-undo logging: This level of recoverability only guarantees that committed transactions are durable, but does not provide the ability to undo the effects of uncommitted transactions.
  • Undo logging: This level of recoverability provides the ability to undo the effects of uncommitted transactions but may result in the loss of updates made by committed transactions that occur after the failed transaction.
  • Redo logging: This level of recoverability provides the ability to redo the effects of committed transactions, ensuring that all committed updates are durable and can be recovered in the event of failure.
  • Undo-redo logging: This level of recoverability provides both undo and redo capabilities, ensuring that the system can recover to a consistent state regardless of whether a transaction has been committed or not.

In addition to these levels of recoverability, database systems may also use techniques such as checkpointing and shadow paging to improve recovery performance and reduce the overhead associated with logging.

Overall, recoverability is a crucial property of database systems, as it ensures that data is consistent and durable even in the event of failures or errors. It is important for database administrators to understand the level of recoverability provided by their system and to configure it appropriately to meet their application's requirements.

schedules_types

Recoverable Schedules

A recoverable schedule in DBMS ensures that a transaction commits only after all transactions it depends on have committed. This prevents inconsistencies and ensures the database can recover correctly after failures. It maintains data integrity by avoiding scenarios where a committed transaction relies on an uncommitted or aborted one.

Example 1:

Consider the following schedule involving two transactions T1 and T2.

T1T2
R(A) 
W(A) 
 W(A)
 R(A)
commit 
 commit

This is a recoverable schedule since T1 commits before T2, that makes the value read by T2 correct.

Example 2:

S1: R1(x), W1(x), R2(x), R1(y), R2(y),W2(x), W1(y), C1, C2;

cascade_3
  • T2 reads uncommitted data from T1 (R2(x) depends on W1(x)), but T2 commits only after T1 commits.
  • The schedule is recoverable.

Read more about Types of Schedule Based on Recoverability.

Irrecoverable Schedules

An irrecoverable schedule occurs when a transaction commits after performing a dirty read—i.e., reading data written by another uncommitted transaction—and the original transaction later fails or is rolled back. This leads to inconsistency, as the committed transaction has used invalid data.

For example, if T2 reads and commits a value written by T1, but T1 later fails, the system cannot undo T2 since it has already committed. This makes the schedule irrecoverable. To avoid this, a transaction should not commit before the transactions it depends on have committed.Recoverabilityofschedules

Recoverable with Cascading Rollback

A recoverable schedule with cascading rollback occurs when a failure in one transaction (Ti) causes other dependent transactions (Tj) to also roll back, but no committed transaction is affected. Since Tj reads data written by Ti and has not yet committed, it can be safely rolled back when Ti fails.

This preserves recoverability, as all dependencies commit in the correct order. Although multiple rollbacks may happen, the database remains consistent. Such a schedule follows the rule: Tj commits only after Ti commits.

Recoverabilityofschedules2

Cascadeless Recoverable Rollback

A cascadeless recoverable schedule is a type of transaction schedule where transactions are both recoverable and free from cascading rollbacks. In this schedule, a transaction (Tj) reads data written by another transaction (Ti) only after Ti has committed.

This ensures that if Ti fails, no other transaction depends on its uncommitted changes, avoiding the need for cascading rollbacks. The schedule maintains consistency and simplifies recovery by preventing dirty reads. The key rule is: Tj reads Ti’s data only after Ti commits, ensuring both recoverability and cascadelessness.

Recoverability3

Capabilities of Recoverability in DBMS

  1. Atomicity: Transactions in a DBMS are atomic, meaning they either complete entirely or are rolled back to their original state in case of a failure. This ensures that the database remains in a consistent state at all times.
  2. Durability: Once a transaction is committed, its changes are permanently saved to the database. Even in the event of a failure, these changes are retained, ensuring the database can be restored to its last consistent state.
  3. Logging: A DBMS maintains a transaction log that records all changes made to the database and the transactions responsible for those changes. In case of a failure, this log is used to recover the database to a consistent state.
  4. Checkpointing: Checkpoints mark a specific point in time where the DBMS saves the current state of the database. This reduces recovery time after a failure, as only the transactions occurring after the last checkpoint need to be rolled back or replayed.
  5. Recovery Manager: The recovery manager is a component of the DBMS responsible for restoring the database to a consistent state after a failure. It uses logs and checkpoints to identify and handle transactions that need to be undone or redone.
  6. Media Recovery: Media recovery deals with recovering the database from storage failures, such as a hard drive crash. This involves restoring the database from backups and using transaction logs to bring it up to date.

Next Article
Implementation of Locking in DBMS

K

kartik
Improve
Article Tags :
  • DBMS
  • DBMS-Transactions and Concurrency Control

Similar Reads

    DBMS Tutorial – Learn Database Management System
    Database Management System (DBMS) is a software used to manage data from a database. A database is a structured collection of data that is stored in an electronic device. The data can be text, video, image or any other format.A relational database stores data in the form of tables and a NoSQL databa
    7 min read

    Basic of DBMS

    Introduction of DBMS (Database Management System)
    A Database Management System (DBMS) is a software solution designed to efficiently manage, organize, and retrieve data in a structured manner. It serves as a critical component in modern computing, enabling organizations to store, manipulate, and secure their data effectively. From small application
    8 min read
    History of DBMS
    The first database management systems (DBMS) were created to handle complex data for businesses in the 1960s. These systems included Charles Bachman's Integrated Data Store (IDS) and IBM's Information Management System (IMS). Databases were first organized into tree-like structures using hierarchica
    7 min read
    DBMS Architecture 1-level, 2-Level, 3-Level
    A database stores important information that needs to be accessed quickly and securely. Choosing the right DBMS architecture is essential for organizing, managing, and maintaining the data efficiently. It defines how users interact with the database to read, write, or update information. The schema
    7 min read
    Difference between File System and DBMS
    A file system and a DBMS are two kinds of data management systems that are used in different capacities and possess different characteristics. A File System is a way of organizing files into groups and folders and then storing them in a storage device. It provides the media that stores data as well
    6 min read

    Entity Relationship Model

    Introduction of ER Model
    The Entity-Relationship Model (ER Model) is a conceptual model for designing a databases. This model represents the logical structure of a database, including entities, their attributes and relationships between them. Entity: An objects that is stored as data such as Student, Course or Company.Attri
    10 min read
    Structural Constraints of Relationships in ER Model
    Structural constraints, within the context of Entity-Relationship (ER) modeling, specify and determine how the entities take part in the relationships and this gives an outline of how the interactions between the entities can be designed in a database. Two primary types of constraints are cardinalit
    5 min read
    Generalization, Specialization and Aggregation in ER Model
    Using the ER model for bigger data creates a lot of complexity while designing a database model, So in order to minimize the complexity Generalization, Specialization, and Aggregation were introduced in the ER model. These were used for data abstraction. In which an abstraction mechanism is used to
    4 min read
    Introduction of Relational Model and Codd Rules in DBMS
    The Relational Model is a fundamental concept in Database Management Systems (DBMS) that organizes data into tables, also known as relations. This model simplifies data storage, retrieval, and management by using rows and columns. Codd’s Rules, introduced by Dr. Edgar F. Codd, define the principles
    14 min read
    Types of Keys in Relational Model (Candidate, Super, Primary, Alternate and Foreign)
    In the context of a relational database, Keys are one of the basic requirements of a relational database model. keys are fundamental components that ensure data integrity, uniqueness, and efficient access. It is widely used to identify the tuples(rows) uniquely in the table. We also use keys to set
    8 min read
    Mapping from ER Model to Relational Model
    Converting an Entity-Relationship (ER) diagram to a Relational Model is a crucial step in database design. The ER model represents the conceptual structure of a database, while the Relational Model is a physical representation that can be directly implemented using a Relational Database Management S
    7 min read
    Strategies for Schema design in DBMS
    There are various strategies that are considered while designing a schema. Most of these strategies follow an incremental approach that is, they must start with some schema constructs derived from the requirements and then they incrementally modify, refine, or build on them. In this article, let's d
    7 min read

    Relational Model

    Introduction of Relational Algebra in DBMS
    Relational Algebra is a formal language used to query and manipulate relational databases, consisting of a set of operations like selection, projection, union, and join. It provides a mathematical framework for querying databases, ensuring efficient data retrieval and manipulation. Relational algebr
    9 min read
    SQL Joins (Inner, Left, Right and Full Join)
    SQL joins are fundamental tools for combining data from multiple tables in relational databases. Joins allow efficient data retrieval, which is essential for generating meaningful observations and solving complex business queries. Understanding SQL join types, such as INNER JOIN, LEFT JOIN, RIGHT JO
    5 min read
    Join operation Vs Nested query in DBMS
    The growth of technology and automation coupled with exponential amounts of data has led to the importance and omnipresence of databases which, simply put, are organized collections of data. Considering a naive approach, one can theoretically keep all the data in one large table, however that increa
    5 min read
    Tuple Relational Calculus (TRC) in DBMS
    Tuple Relational Calculus (TRC) is a non-procedural query language used in relational database management systems (RDBMS) to retrieve data from tables. TRC is based on the concept of tuples, which are ordered sets of attribute values that represent a single row or record in a database table. TRC is
    4 min read
    Domain Relational Calculus in DBMS
    Domain Relational Calculus is a non-procedural query language equivalent in power to Tuple Relational Calculus. Domain Relational Calculus provides only the description of the query but it does not provide the methods to solve it. In Domain Relational Calculus, a query is expressed as, { < x1, x2
    2 min read

    Relational Algebra

    Introduction of Relational Algebra in DBMS
    Relational Algebra is a formal language used to query and manipulate relational databases, consisting of a set of operations like selection, projection, union, and join. It provides a mathematical framework for querying databases, ensuring efficient data retrieval and manipulation. Relational algebr
    9 min read
    SQL Joins (Inner, Left, Right and Full Join)
    SQL joins are fundamental tools for combining data from multiple tables in relational databases. Joins allow efficient data retrieval, which is essential for generating meaningful observations and solving complex business queries. Understanding SQL join types, such as INNER JOIN, LEFT JOIN, RIGHT JO
    5 min read
    Join operation Vs Nested query in DBMS
    The growth of technology and automation coupled with exponential amounts of data has led to the importance and omnipresence of databases which, simply put, are organized collections of data. Considering a naive approach, one can theoretically keep all the data in one large table, however that increa
    5 min read
    Tuple Relational Calculus (TRC) in DBMS
    Tuple Relational Calculus (TRC) is a non-procedural query language used in relational database management systems (RDBMS) to retrieve data from tables. TRC is based on the concept of tuples, which are ordered sets of attribute values that represent a single row or record in a database table. TRC is
    4 min read
    Domain Relational Calculus in DBMS
    Domain Relational Calculus is a non-procedural query language equivalent in power to Tuple Relational Calculus. Domain Relational Calculus provides only the description of the query but it does not provide the methods to solve it. In Domain Relational Calculus, a query is expressed as, { < x1, x2
    2 min read

    Functional Dependencies & Normalization

    Functional Dependency and Attribute Closure
    Functional dependency and attribute closure are essential for maintaining data integrity and building effective, organized, and normalized databases.Functional DependencyA functional dependency A->B in a relation holds if two tuples having the same value of attribute A must have the same value fo
    5 min read
    Armstrong's Axioms in Functional Dependency in DBMS
    Armstrong's Axioms refer to a set of inference rules, introduced by William W. Armstrong, that are used to test the logical implication of functional dependencies. Given a set of functional dependencies F, the closure of F (denoted as F+) is the set of all functional dependencies logically implied b
    4 min read
    Canonical Cover of Functional Dependencies in DBMS
    Managing a large set of functional dependencies can result in unnecessary computational overhead. This is where the canonical cover becomes useful. The canonical cover of a set of functional dependencies F is a simplified version of F that retains the same closure as the original set, ensuring no re
    7 min read
    Normal Forms in DBMS
    In the world of database management, Normal Forms are important for ensuring that data is structured logically, reducing redundancy, and maintaining data integrity. When working with databases, especially relational databases, it is critical to follow normalization techniques that help to eliminate
    7 min read
    The Problem of Redundancy in Database
    Redundancy means having multiple copies of the same data in the database. This problem arises when a database is not normalized. Suppose a table of student details attributes is: student ID, student name, college name, college rank, and course opted. Student_ID Name Contact College Course Rank 100Hi
    6 min read
    Lossless Join and Dependency Preserving Decomposition
    Decomposition of a relation is done when a relation in a relational model is not in appropriate normal form. Relation R is decomposed into two or more relations if decomposition is lossless join as well as dependency preserving. Lossless Join DecompositionIf we decompose a relation R into relations
    4 min read
    Denormalization in Databases
    Denormalization focuses on combining multiple tables to make queries execute quickly. It adds redundancies in the database though. In this article, we’ll explore Denormalization and how it impacts database design. This method can help us to avoid costly joins in a relational database made during nor
    6 min read

    Transactions & Concurrency Control

    ACID Properties in DBMS
    In the world of DBMS, transactions are fundamental operations that allow us to modify and retrieve data. However, to ensure the integrity of a database, it is important that these transactions are executed in a way that maintains consistency, correctness, and reliability. This is where the ACID prop
    8 min read
    Types of Schedules in DBMS
    Schedule, as the name suggests, is a process of lining the transactions and executing them one by one. When there are multiple transactions that are running in a concurrent manner and the order of operation is needed to be set so that the operations do not overlap each other, Scheduling is brought i
    7 min read
    Recoverability in DBMS
    Recoverability is a critical feature of database systems. It ensures that after a failure, the database returns to a consistent state by permanently saving committed transactions and rolling back uncommitted ones. It relies on transaction logs to undo or redo changes as needed. This is crucial in mu
    6 min read
    Implementation of Locking in DBMS
    Locking protocols are used in database management systems as a means of concurrency control. Multiple transactions may request a lock on a data item simultaneously. Hence, we require a mechanism to manage the locking requests made by transactions. Such a mechanism is called a Lock Manager. It relies
    5 min read
    Deadlock in DBMS
    In a Database Management System (DBMS), a deadlock occurs when two or more transactions are waiting indefinitely for one another to release resources (such as locks on tables, rows, or other database objects). This results in a situation where none of the transactions can proceed, effectively bringi
    8 min read
    Starvation in DBMS
    Starvation in DBMS is a problem that happens when some processes are unable to get the resources they need because other processes keep getting priority. This can happen in situations like locking or scheduling, where some processes keep getting the resources first, leaving others waiting indefinite
    8 min read

    Advanced DBMS

    Indexing in Databases - Set 1
    Indexing is a crucial technique used in databases to optimize data retrieval operations. It improves query performance by minimizing disk I/O operations, thus reducing the time it takes to locate and access data. Essentially, indexing allows the database management system (DBMS) to locate data more
    8 min read
    Introduction of B-Tree
    A B-Tree is a specialized m-way tree designed to optimize data access, especially on disk-based storage systems. In a B-Tree of order m, each node can have up to m children and m-1 keys, allowing it to efficiently manage large datasets.The value of m is decided based on disk block and key sizes.One
    8 min read
    Introduction of B+ Tree
    B + Tree is a variation of the B-tree data structure. In a B + tree, data pointers are stored only at the leaf nodes of the tree. In this tree, structure of a leaf node differs from the structure of internal nodes. The leaf nodes have an entry for every value of the search field, along with a data p
    8 min read
    Bitmap Indexing in DBMS
    Bitmap Indexing is a data indexing technique used in database management systems (DBMS) to improve the performance of read-only queries that involve large datasets. It involves creating a bitmap index, which is a data structure that represents the presence or absence of data values in a table or col
    8 min read
    Inverted Index
    An Inverted Index is a data structure used in information retrieval systems to efficiently retrieve documents or web pages containing a specific term or set of terms. In an inverted index, the index is organized by terms (words), and each term points to a list of documents or web pages that contain
    7 min read
    SQL Queries on Clustered and Non-Clustered Indexes
    Indexes in SQL play a pivotal role in enhancing database performance by enabling efficient data retrieval without scanning the entire table. The two primary types of indexes Clustered Index and Non-Clustered Index serve distinct purposes in optimizing query performance. In this article, we will expl
    7 min read
    File Organization in DBMS - Set 1
    A database consists of a huge amount of data. The data is grouped within a table in RDBMS, and each table has related records. A user can see that the data is stored in the form of tables, but in actuality, this huge amount of data is stored in physical memory in the form of files. What is a File?A
    6 min read

    DBMS Practice

    Last Minute Notes - DBMS
    Database Management System is an organized collection of interrelated data that helps in accessing data quickly, along with efficient insertion, and deletion of data into the DBMS. DBMS organizes data in the form of tables, schemas, records, etc. DBMS over File System (Limitations of File System)The
    15+ min read
    Top 60 DBMS Interview Questions with Answers for 2025
    A Database Management System (DBMS) is the backbone of modern data storage and management. Understanding DBMS concepts is critical for anyone looking to work with databases. Whether you're preparing for your first job in database management or advancing in your career, being well-prepared for a DBMS
    15+ min read
    Commonly asked DBMS Interview Questions | Set 2
    This article is an extension of Commonly asked DBMS interview questions | Set 1.Q1. There is a table where only one row is fully repeated. Write a Query to find the Repeated rowNameSectionabcCS1bcdCS2abcCS1In the above table, we can find duplicate rows using the below query.SELECT name, section FROM
    5 min read
geeksforgeeks-footer-logo
Corporate & Communications Address:
A-143, 7th Floor, Sovereign Corporate Tower, Sector- 136, Noida, Uttar Pradesh (201305)
Registered Address:
K 061, Tower K, Gulshan Vivante Apartment, Sector 137, Noida, Gautam Buddh Nagar, Uttar Pradesh, 201305
GFG App on Play Store GFG App on App Store
Advertise with us
  • Company
  • About Us
  • Legal
  • Privacy Policy
  • In Media
  • Contact Us
  • Advertise with us
  • GFG Corporate Solution
  • Placement Training Program
  • Languages
  • Python
  • Java
  • C++
  • PHP
  • GoLang
  • SQL
  • R Language
  • Android Tutorial
  • Tutorials Archive
  • DSA
  • Data Structures
  • Algorithms
  • DSA for Beginners
  • Basic DSA Problems
  • DSA Roadmap
  • Top 100 DSA Interview Problems
  • DSA Roadmap by Sandeep Jain
  • All Cheat Sheets
  • Data Science & ML
  • Data Science With Python
  • Data Science For Beginner
  • Machine Learning
  • ML Maths
  • Data Visualisation
  • Pandas
  • NumPy
  • NLP
  • Deep Learning
  • Web Technologies
  • HTML
  • CSS
  • JavaScript
  • TypeScript
  • ReactJS
  • NextJS
  • Bootstrap
  • Web Design
  • Python Tutorial
  • Python Programming Examples
  • Python Projects
  • Python Tkinter
  • Python Web Scraping
  • OpenCV Tutorial
  • Python Interview Question
  • Django
  • Computer Science
  • Operating Systems
  • Computer Network
  • Database Management System
  • Software Engineering
  • Digital Logic Design
  • Engineering Maths
  • Software Development
  • Software Testing
  • DevOps
  • Git
  • Linux
  • AWS
  • Docker
  • Kubernetes
  • Azure
  • GCP
  • DevOps Roadmap
  • System Design
  • High Level Design
  • Low Level Design
  • UML Diagrams
  • Interview Guide
  • Design Patterns
  • OOAD
  • System Design Bootcamp
  • Interview Questions
  • Inteview Preparation
  • Competitive Programming
  • Top DS or Algo for CP
  • Company-Wise Recruitment Process
  • Company-Wise Preparation
  • Aptitude Preparation
  • Puzzles
  • School Subjects
  • Mathematics
  • Physics
  • Chemistry
  • Biology
  • Social Science
  • English Grammar
  • Commerce
  • World GK
  • GeeksforGeeks Videos
  • DSA
  • Python
  • Java
  • C++
  • Web Development
  • Data Science
  • CS Subjects
@GeeksforGeeks, Sanchhaya Education Private Limited, All rights reserved
We use cookies to ensure you have the best browsing experience on our website. By using our site, you acknowledge that you have read and understood our Cookie Policy & Privacy Policy
Lightbox
Improvement
Suggest Changes
Help us improve. Share your suggestions to enhance the article. Contribute your expertise and make a difference in the GeeksforGeeks portal.
geeksforgeeks-suggest-icon
Create Improvement
Enhance the article with your expertise. Contribute to the GeeksforGeeks community and help create better learning resources for all.
geeksforgeeks-improvement-icon
Suggest Changes
min 4 words, max Words Limit:1000

Thank You!

Your suggestions are valuable to us.

What kind of Experience do you want to share?

Interview Experiences
Admission Experiences
Career Journeys
Work Experiences
Campus Experiences
Competitive Exam Experiences