It is the process that allows data to be stored, retrieved and manipulated efficiently. As enterprises and individuals continue to create more data than ever, it is crucial that we are able adequately manage this information with ease. Introduction In this paper we have given an overview of database management systems types and applications, where how modern databases are used by the world.
What is Database Management?
Database management refers to a method of control that involves the collection, organization and storage data using software designed for these purposes- database Management System DBMS. Database is a structured method of storing data with stored informations for easy access.
DBMS: The most basic goal of a database management system is to ensure that data remains consistent and available, secure from attacks by unauthorized people or processes, at least when necessary. DBMS come in all shapes and sizes, ranging from small one-user database design to large enterprise systems like an SQL Server for a multinational big company.
1. Database Management Systems Relational Database Management System RDBMS: The RDMBS is a general-purpose database management system used by many different applications in industry today. They are organized as tables, and these tables can have relationships created by linking two or more keys. These databases can be accessed using a language called SQL Structured Query Language. There are many popular RDBMSs like MySQL, PostgreSQL or Oracle and even Microsoft SQL Server. Relational databases are praised for their robustness, ACID Atomicity, Consistency, Isolation, Durability compliant and suitability to handle many problems involving data.
2. NoSQL Databases: But where we have unstructured or semi-structure data NoSQL databases are good to use.And for the Case studies like Highly Scalable, highly availability and more flexible than relational model because of REST. There are different types of NoSQL databases, because they typically do not fit into the following data model: document store (simple like MongoDB), key-value stores( minimalistic with few queries capable such as Redis ),wide-columnar stor(allows for massive scale out) and graphtores(neo4j). NoSQL Databases: Reading about one of the most popular NoSQL Database required to solve performance and Scalability on Large Scale Distributed systems like Real-time analytic; Social media channel etc.
3. Object oriented databases: An object model is a data structure as an entirely separate way to use OOP, though in the same language it was first constructed for. These are database management systems (DBMS) which support complex data models such as objects that have methods and properties just like classes do in programming languages or semi-structured extended entity relationship modeling capabilities also available even when they were coupled with OO development environments built on compatible persistency mechanisms thereby allowing them handle more functionally demanding business application areas where logic components bound closely around persistence operations executed at runtime could bring about most benefit from implementors of these solutions running today since there would be no need either permit multiple calls between two processes simultaneously chatting one another whether needed leverage greater speed depend heavily upon proximity synchronization points among concurrent actors themselves synchronized towards ensuring none refused service calm cool confidence given turn coming sooner soonest based providing immediate availability choices made beforehand certain highly critical tasks looked after elsewhere advance offer peace mind ever streamlined ahead once again turning falling prey downed system incompleteness security constraints back fully operational beyond any limit whatever mentioned wedded moment prior usage best possible durability guarantees whilst still being able provide reasonable assurance thereof gave comfort than prevails under stealthiest demands come our direction burgeoning insidious long-held silent zeal… Object oriented databases are db4o, Object DB.
4. Hierarchical and the Network Databases: Hierarchical databases arrange data in a tree-like model, where each record has one owner (top entity) but possible many dependants nodes. This model is not as flexible than the traditional databases but could be great for some kind of data organization charts, file structures …. Graph stores/network databases provide nodes, edges and properties to represent and store data where relationships are as important as the record itself. A number of these are outdated models, still in use with some legacy systems and also specialized applications.
APP FOR DATABASE MANAGEMENT
1. Enterprise Database Management: In the business database control,maintains all of your records,consumer information and merchandise transactions. Most large companies would have definitely installed robust ERP systems and CRM applications, which rely on clean data for optimal functionality.
2. They even use the data so that it can be a part of the database work, to store user accounts and other content and dynamic date in modern web applications or mobile apps. Along with that, the performance and efficiencies of these applications greatly depend on the DBMS they are running on.
3. Big Data with Analytics which no more an alien term where the big data is created in a stack of organizations and then analysed to mine insights out it. Big data analytics in companies rely on database management systems like Hadoop and Apache Spark which store, manage, process large datasets.
4. Healthcare and Government: Healthcare providers or government agencies require databases for storing patient records, public record etc. Security, validating data accuracy (involving many constraints) requirement to comply with laws such as HIPAA are the primary responsibilities of a DBA in these areas.
Problems with Database Management Despite great strides in database technology, many challenges continue to confront the management of databases:
1. Databases have to be able to store and query large amounts of data at scale but this has to be a smart move and probably in the lines of distributed databases or may cloud solution.
2. Security: Security is of utmost concern in database management as the lack of security can make sensitive data vulnerable to theft and misuse. Crucial personal information…is something that should be protected with multiple levels of security encrypting the data, access controls and regular security audits.
3. Performance: Databases should be able to process queries and transactions as quick as possible, even more so under heavy loads due to the application itself will do all of this. Mode fine tuning your database queries, indexing or even some resource optimization of your underlying hardware racks.
4. Consistency and Data Integrity-When the replication workloads of concurrent transactions involve keeping data consistency across multiple instances in distributed systems.
5. Disaster Backup and Recovery Backing up of data to ensure that it can be restored right in case the system faces a failure or disaster.
Conclusion
For any Applications that we build, it needs database to save and retrieve the date inside which makes as a backbone of modern development. As per Industry Requirement, Different DBMSs are used starting from relational databases to NoSQL systems. The sheer amount that this data expands and its speed grows to geometric proportions, approaching at a million miles per hour is why it becomes absolutely crucial to have proper database management in place so applications running off of such sets can do so securely under the considerable load. But it is in the end a situation that calls for us to remember over time general, the database technology keeps getting better so we incrementally get better at data management and leveraging our historic asset of lock in data with compelling new ways to delight customers as if organizations are pulling themselves free from their own archaic standby you drown now lakes of legacy databases.