Non-Volatile Storage in DBMS
Last Updated :
23 Jul, 2025
An integral part of the DBMS world is non-volatile storage, which is responsible for keeping information reliable and longer-lasting. This article focuses on high-detailed knowledge about DBMS non-volatile storage systems, comprising definitions, explanations, and insights by only using the material written by oneself and not copying from third parties.
What is Non-Volatile Storage?
Non-volatile storage is a basic in-concept database management systems theory, which implies the existence of storage devices capable of keeping data even if the power is off. Contrastingly, volatile storage does not operate when electric power is disrupted; however, non-volatile storage guarantees data reliability, durability as well as data integrity, which increases the importance of such storage systems in maintaining data consistency.
Key Terminologies
Non-Volatile Storage
It is when data is stored and kept in storage devices even without power. Device examples include Hard Disk Drives (HDDs) analogs such as CDs and DVDs,- Solid State Drives (SSDs), and the like, as well as Flash Drives such as USB drives. Volatile storage implies that the data remains rooted whereas it also permits it to be accessible over long periods when non-volatile storage is not there.
Volatile Storage
In a different from the non-volatile storage, the volatile storage includes temporary storage devices that can't save working memory when there is a power failure or shutdown. The first paradigm for change is known as Random Access Memory (RAM), which applies to volatile storage. RAM resides in the space that takes care of intermediate storage which is very fast and easy to use as well but data is unstable and must be saved to a storage media in order for information to be permanently kept.
Data Durability
This term means data's ability to remain intact, resisting system failures, power outages, or crashes. In other words, it means that data will not lose or get corrupted. The persistent nature of non-volatile storage is critical for ensuring the safety of data by retaining it despite availability of power points.
Persistence
Persistence refers to the persistence of data by its being stored for the same time frame and whether the system states are different. To guarantee that data is maintained permanently non-volatile storage devices use persistent storage (past system shutdowns and reboots data still can be accessed).
Secondary Storage
Non-volatile storage, being a typical of DBMS’s secondary storage, is said to have some kind of persistence and is stored outside the volatile random access memory (RAM). This is actually a good thing because it supports primary (souches as RAM) by providing for the larger, longterm storage capacity being a persitent storage space. While typical storage devices such as HDD and SSD are used for databases, files and persistent data in a DBMS, different memory types are required to access this information.
Backup
Backup is an activity of creating duplicates of data stored on the non-volatile data storage devices whose aim is to avoid losing data. The primary function of designacy backups in DBMS is to maintain data integrity and facilitate recovery if there is a hardware failure, natural disaster or inadvertent data loss.
Redundancy
The occurrence of redundancy by duplicating data or utilizing extra-bound storage components in the DBMS leads to high data availability and fault tolerance. Technologies like RAID (Redundant Array of Independent Disks) are used to establish pro-adaptable storage structure that can tolerate the situations of the failed disks without data loss.
Transaction Logging
Recording is the technique used in DBMS to store all changes occurs in the database during transactions. Through keeping data operations log (include inserts, updates, as well as deletes) database management systems (DBMS) are able to go back to system failure or crashes through consistent data recovery.
Explanation and Examples
Volatile storage in the DBMS of a system serves a key purpose to guarantee the safety of the data and its continuity. What if some testing procedure operates on a server and a DBMS is there? The memory part where data is residing is called the volatile memory (RAM). Database operations needs to perform their activities there. This kind of memory, however, is a volatile one that undergoes a reset process once power is interrupted.
In order to do this obstacle, DBMS implements non-volatile storage devices such as the hard disk drives (HDDs) and solid state drives (SSDs), which are used to store data permanently. Provided by these storage systems, data remains intact even the power outage or the system shutdown occurs; this is a guarantee for data durability and continuity.
A DBMS allows entry and storage of data by users as tables, indexes, and other objects in non-volatile storage units. DBMS would track and apply the changes done by users via its commands, including input, update, or query, returning data to non-volatile storage so that any data modification survives at system rebooting.
Steps to Ensure Data Persistence
While DBMS inherently utilizes non-volatile storage for data persistence, certain steps can enhance data durability and reliability:
- Regular Backups: Frequent backups of database files to either non-volatile storage devices or cloud storage services should be scheduled to limit the risk of data loss state of affairs.
- Redundancy: Codify data redundancy strategies by using RAID (Redundant Array of Independent Disks) to maintain data availability as well as fault tolerance ability.
- Database Recovery: Configure DBMS for the automated recovery and transaction logging so that the data can be reverted to the previous state in a failure or crash.
- Monitoring and Maintenance: Monitor storage devices; perform such maintenance tasks like cleaning the drives; report and resolve disk issues in time thereby preventing any data corruption or loss.
Conclusion
Volatile storage is a prerequisite of connectivity between data persistence and data durability in DBMS, this way the data will remain intact without any interruption. Comprehend the distinctness of Backup-Restoration concept, and specially use suitable storage solutions, as well as protect the database using data protection measures are crucial parts that constitute a robust and reliable database environment. Through the strategy of deploying storage access properly to the data they need, organizations can secure their valuable databases assets and faultless database operations.
Similar Reads
DBMS Tutorial â 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)DBMS is a software system that manages, stores, and retrieves data efficiently in a structured format.It allows users to create, update, and query databases efficiently.Ensures data integrity, consistency, and security across multiple users and applications.Reduces data redundancy and inconsistency
6 min read
History of DBMSThe 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-LevelA DBMS architecture defines how users interact with the database to read, write, or update information. A well-designed architecture and schema (a blueprint detailing tables, fields and relationships) ensure data consistency, improve performance and keep data secure.Types of DBMS Architecture There
6 min read
Difference between File System and DBMSA 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 ModelThe 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 ModelStructural 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 ModelUsing 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 h
4 min read
Introduction of Relational Model and Codd Rules in DBMSThe 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. Coddâs Rules, introduced by Dr. Edgar F. Codd, define the principles
14 min read
Keys in Relational ModelIn 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 u
6 min read
Mapping from ER Model to Relational ModelConverting 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 DBMSThere 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. What is Schema Design?Sch
6 min read
Relational Model
Introduction of Relational Algebra in DBMSRelational 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. For example, consider two tables where one table (say Student) has student information with id as a key and other table (say Marks) has information about marks of every student id. Now to display the mar
4 min read
Join operation Vs Nested query in DBMSThe concept of joins and nested queries emerged to facilitate the retrieval and management of data stored in multiple, often interrelated tables within a relational database. As databases are normalized to reduce redundancy, the meaningful information extracted often requires combining data from dif
3 min read
Tuple Relational Calculus (TRC) in DBMSTuple Relational Calculus (TRC) is a non-procedural query language used to retrieve data from relational databases by describing the properties of the required data (not how to fetch it). It is based on first-order predicate logic and uses tuple variables to represent rows of tables.Syntax: The basi
4 min read
Domain Relational Calculus in DBMSDomain Relational Calculus (DRC) is a formal query language for relational databases. It describes queries by specifying a set of conditions or formulas that the data must satisfy. These conditions are written using domain variables and predicates, and it returns a relation that satisfies the specif
4 min read
Relational Algebra
Introduction of Relational Algebra in DBMSRelational 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. For example, consider two tables where one table (say Student) has student information with id as a key and other table (say Marks) has information about marks of every student id. Now to display the mar
4 min read
Join operation Vs Nested query in DBMSThe concept of joins and nested queries emerged to facilitate the retrieval and management of data stored in multiple, often interrelated tables within a relational database. As databases are normalized to reduce redundancy, the meaningful information extracted often requires combining data from dif
3 min read
Tuple Relational Calculus (TRC) in DBMSTuple Relational Calculus (TRC) is a non-procedural query language used to retrieve data from relational databases by describing the properties of the required data (not how to fetch it). It is based on first-order predicate logic and uses tuple variables to represent rows of tables.Syntax: The basi
4 min read
Domain Relational Calculus in DBMSDomain Relational Calculus (DRC) is a formal query language for relational databases. It describes queries by specifying a set of conditions or formulas that the data must satisfy. These conditions are written using domain variables and predicates, and it returns a relation that satisfies the specif
4 min read
Functional Dependencies & Normalization
Attribute Closure in DBMSFunctional dependency and attribute closure are essential for maintaining data integrity and building effective, organized and normalized databases. Attribute closure of an attribute set can be defined as set of attributes which can be functionally determined from it.How to find attribute closure of
4 min read
Armstrong's Axioms in Functional Dependency in DBMSArmstrong'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 DBMSManaging a large set of functional dependencies can result in unnecessary computational overhead. This is where the canonical cover becomes useful. A canonical cover is a set of functional dependencies that is equivalent to a given set of functional dependencies but is minimal in terms of the number
7 min read
Normal Forms in DBMSIn 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 DatabaseRedundancy 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 DecompositionDecomposition 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 DatabasesDenormalization is a database optimization technique in which we add redundant data to one or more tables. This can help us avoid costly joins in a relational database. Note that denormalization does not mean 'reversing normalization' or 'not to normalize'. It is an optimization technique that is ap
4 min read
Transactions & Concurrency Control
ACID Properties in DBMSTransactions 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 even in case of failures / errors. This is where t
5 min read
Types of Schedules in DBMSScheduling is the process of determining the order in which transactions are executed. When multiple transactions run concurrently, scheduling ensures that operations are executed in a way that prevents conflicts or overlaps between them.There are several types of schedules, all of them are depicted
6 min read
Recoverability in DBMSRecoverability ensures that after a failure, the database can restore a consistent state by keeping committed changes and undoing uncommitted ones. It uses logs to redo or undo actions, preventing data loss and maintaining integrity.There are several levels of recoverability that can be supported by
5 min read
Implementation of Locking in DBMSLocking 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 DBMSA deadlock occurs in a multi-user database environment when two or more transactions block each other indefinitely by each holding a resource the other needs. This results in a cycle of dependencies (circular wait) where no transaction can proceed.For Example: Consider the image belowDeadlock in DBM
4 min read
Starvation in DBMSStarvation 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 DatabasesIndexing in DBMS is used to speed up data retrieval by minimizing disk scans. Instead of searching through all rows, the DBMS uses index structures to quickly locate data using key values.When an index is created, it stores sorted key values and pointers to actual data rows. This reduces the number
6 min read
Introduction of B TreeA 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+ TreeA B+ Tree is an advanced data structure used in database systems and file systems to maintain sorted data for fast retrieval, especially from disk. It is an extended version of the B Tree, where all actual data is stored only in the leaf nodes, while internal nodes contain only keys for navigation.C
5 min read
Bitmap Indexing in DBMSBitmap Indexing is a powerful data indexing technique used in Database Management Systems (DBMS) to speed up queries- especially those involving large datasets and columns with only a few unique values (called low-cardinality columns).In a database table, some columns only contain a few different va
3 min read
Inverted IndexAn 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 IndexesIndexes 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 DBMSFile organization in DBMS refers to the method of storing data records in a file so they can be accessed efficiently. It determines how data is arranged, stored, and retrieved from physical storage.The Objective of File OrganizationIt helps in the faster selection of records i.e. it makes the proces
5 min read
DBMS Practice