What is Data?
Data is a collection of a distinct small unit of information. It can be used in a variety of forms like text, numbers, media, bytes, etc. it can be stored in pieces of paper or electronic memory, etc. Word ‘Data’ is originated from the word ‘datum’ that means ‘single piece of information.’ It is plural of the word datum. In computing, Data is information that can be translated into a form for efficient movement and processing. Data is interchangeable.
What is Database?
A database is an organized collection of data, so that it can be easily accessed and You can organize data into tables, rows, columns, and index it to make it easier to find relevant information. Database handlers create a database in such a way that only one set of software program provides access of data to all the users. The main purpose of the database is to operate a large amount of information by storing, retrieving, and managing data. There are many dynamic websites on the World Wide Web nowadays which are handled through databases. For example, a model that checks the availability of rooms in a hotel. It is an example of a dynamic website that uses a database. There are many databases available like MySQL, Sybase, Oracle, MongoDB, Informix, PostgreSQL, SQL Server, etc. Modern databases are managed by the database management system (DBMS). SQL or Structured Query Language is used to operate on the data stored in a database. SQL depends on relational algebra and tuple relational calculus. A cylindrical structure is used to display the image of a database.
Purpose of Database Systems
The main purpose of database systems is to manage the data. Consider a university that keeps the data of students, teachers, courses, books etc. To manage this data we need to store this data somewhere where we can add new data, delete unused data, update outdated data, retrieve data, to perform these operations on data we need a Database management system that allows us to store the data in such a way so that all these operations can be performed on the data efficiently.
What is the need for a Database?
The database systems that we use in our day-to-day life should be able to perform basic CRUD operations. When we think of a supermarket we can visualize the variety of products available but imagine how difficult it would become to handle the same if they don’t have a proper database. Everything would be a Brownian motion if the price of each commodity is not already in the system and instead the billing agent needs to remember or manually check the price of each. Also, we need to make sure that our system or database is stable and can handle the multiple queries being made on it regularly.
Evolution of Databases
The database has completed more than 50 years of journey of its evolution from flat-file system to relational and objects relational systems. It has gone through several generations.
1968 was the year when File-Based database were introduced. In file-based databases, data was maintained in a flat file. Though files have many advantages, there are several limitations. One of the major advantages is that the file system has various access methods, e.g., sequential, indexed, and random. It requires extensive programming in a third-generation language such as COBOL, BASIC.
Hierarchical Data Model
1968-1980 was the era of the Hierarchical Database. Prominent hierarchical database model was IBM’s first DBMS. It was called IMS (Information Management System). In this model, files are related in a parent/child manner.
Below diagram represents Hierarchical Data Model. Small circle represents objects.
Like file system, this model also had some limitations like complex implementation, lack structural independence, can’t easily handle a many-many relationship, etc.
Network data model
Charles Bachman developed the first DBMS at Honeywell called Integrated Data Store (IDS). It was developed in the early 1960s, but it was standardized in 1971 by the CODASYL group (Conference on Data Systems Languages). In this model, files are related as owners and members, like to the common network model.
Network data model identified the following components:
- Network schema (Database organization)
- Sub-schema (views of database per user)
- Data management language (procedural)
This model also had some limitations like system complexity and difficult to design and maintain.
1970 – Present: It is the era of Relational Database and Database Management. In 1970, the relational model was proposed by E.F. Codd. Relational database model has two main terminologies called instance and schema. The instance is a table with rows or columns Schema specifies the structure like name of the relation, type of each column and name. The first internet database application had been created in 1995. During the era of the relational database, many more models had introduced like object-oriented model, object-relational model, etc.
Cloud database facilitates you to store, manage, and retrieve their structured, unstructured data via a cloud platform. This data is accessible over the Internet. Cloud databases are also called a database as service (DBaaS) because they are offered as a managed service.
Some best cloud options are:
- AWS (Amazon Web Services)
- Snowflake Computing
- Oracle Database Cloud Services
- Microsoft SQL server
- Google cloud spanner
Advantages of cloud database
Generally, company provider does not have to invest in databases. It can maintain and support one or more data centers.
Cloud databases are enriched with a variety of automated processes such as recovery, failover, and auto-scaling.
You can access your cloud-based database from any location, anytime. All you need is just an internet connection.
A NoSQL database is an approach to design such databases that can accommodate a wide variety of data models. NoSQL stands for “not only SQL.” It is an alternative to traditional relational databases in which data is placed in tables, and data schema is perfectly designed before the database is built. NoSQL databases are useful for a large set of distributed data.
Some examples of NoSQL database system with their category are:
- MongoDB, CouchDB, Cloudant (Document-based)
- Memcached, Redis, Coherence (key-value store)
- HBase, Big Table, Accumulo (Tabular)
Advantage of NoSQL
NoSQL can handle an extensive amount of data because of scalability. If the data grows, NoSQL database scale it to handle that data in an efficient manner.
NoSQL supports auto replication. Auto replication makes it highly available because, in case of any failure, data replicates itself to the previous consistent state.
Disadvantage of NoSQL
NoSQL is an open-source database, so there is no reliable standard for NoSQL yet.
Data management in NoSQL is much more complicated than relational databases. It is very challenging to install and even more hectic to manage daily.
GUI is not available
GUI tools for NoSQL database are not easily available in the market.
Backup is a great weak point for NoSQL databases. Some databases, like MongoDB, have no powerful approaches for data backup.https://c3bb3781adbc326f284439d12861a7b6.safeframe.googlesyndication.com/safeframe/1-0-38/html/container.html
The Object-Oriented Databases
The object-oriented databases contain data in the form of object and classes. Objects are the real-world entity, and types are the collection of objects. An object-oriented database is a combination of relational model features with objects oriented principles. It is an alternative implementation to that of the relational model. Object-oriented databases hold the rules of object-oriented programming. An object-oriented database management system is a hybrid application. The object-oriented database model contains the following properties.
Object-oriented programming properties
Relational database properties
- Query processing
A graph database is a NoSQL database. It is a graphical representation of data. It contains nodes and edges. A node represents an entity, and each edge represents a relationship between two edges. Every node in a graph database represents a unique identifier. Graph databases are beneficial for searching the relationship between data because they highlight the relationship between relevant data.
Graph databases are very useful when the database contains a complex relationship and dynamic schema.
It is mostly used in supply chain management, identifying the source of IP telephony.
DBMS (Data Base Management System)
Database management System is software which is used to store and retrieve the database. For example, Oracle, MySQL, etc.; these are some popular DBMS tools.
- DBMS provides the interface to perform the various operations like creation, deletion, modification, etc.
- DBMS allows the user to create their databases as per their requirement.
- DBMS accepts the request from the application and provides specific data through the operating system.
- DBMS contains the group of programs which acts according to the user instruction.
- It provides security to the database.
It stores all the data in a single database file, so it can control data redundancy.
An authorized user can share the data among multiple users.
It providesBackup and recovery subsystem. This recovery system creates automatic data from system failure and restores data if required.
Multiple user interfaces
It provides a different type of user interfaces like GUI, application interfaces.
Disadvantage of DBMS
It occupies large disk space and large memory to run efficiently.
DBMS requires a high-speed data processor and larger memory to run DBMS software, so it is costly.
DBMS creates additional complexity and requirements.
RDBMS (Relational Database Management System)
The word RDBMS is termed as ‘Relational Database Management System.’ It is represented as a table that contains rows and column.
RDBMS is based on the Relational model; it was introduced by E. F. Codd.
A relational database contains the following components:
- Record/ Tuple
- Field/Column name /Attribute
An RDBMS is a tabular DBMS that maintains the security, integrity, accuracy, and consistency of the data.
Oracle database came into existence in the late 70s and has many versions available for use. It is compatible with the cloud and is deployable on one or more servers.
Also, the logical data does not affect the physical data. We get an upgraded level of security as the transactions are done in different sessions thus, avoiding any possibility of a clash.
- Provides the latest innovations and features.
- Oracle DBMS tools are incredibly robust thus, capable of performing almost any
- possible task.
- It is an expensive tool for smaller organizations.
- Requires a large number of regular hardware updates.
2. MySQL Database
One of the most popular databases for all the available technological requirements. It is freeware and thus is ideal for both small and large-scale organizations.
MySQL provides us with the choice to configure the data types to accommodate any possible data we have. Also, it is reliable and has no large resources required.
- It is freeware thus cost-efficient.
- Provides a large number of functionalities.
- It supports various user interfaces for easy use.
- Compatible with other DBMS like Oracle and DB2.
- It is a bit slow compared to other DBMS.
- There is no built-in support for OLAP.
- Consumer support is not available for the free version.
3. Microsoft SQL Server
This DBMS works on a cloud-based system or a local server.
Some of the major features include the tracing facility of any changes in the data. It also allows dynamic data masking which helps in protecting the sensitive data stored.
- This is a reliable and fast DBMS.
- Has the ability to adjust to available resources, hence is very resource-efficient.
- Provides easy visualizations for mobile devices.
- Compatible with all Microsoft products.
- This DBMS is very expensive to use.
- Many times leads to hampered resources.
- Not compatible with importing and exporting data files.
4. PostgreSQL Database
One of the major free popular databases and is frequently used in web applications. It supports deployment in various environments i.e. virtual, physical, and cloud-based environments.
The newer versions have support for large volumes of data. Security has also improved.
- A scalable and adjustable DBMS.
- Provide built-in support for the JSON data.
- Provides plenty of predefined functions.
- It is available in various versions of user interfaces.
- Proper documentation is not available.
- The configuration is very confusing and complex.
- Speed hampers due to batch operation of queries.
It is the DBMS that was found by IBM for their internal use and was later released for public use. One of the most important and evident features is faster-skipping technology.
Data skipping helps in increasing the system speed and boosts the effective use of resources. It has added disaster recovery options that increase reliability and compatibility.
- Due to the high-speed, the handling of enormous data becomes easier.
- Compatible with cloud, physical server, or both at the same time.
- Task automation is available as it provides the task scheduler.
- Provides proper error codes and exit codes which make debugging easier.
- Expensive for small organizations or individuals.
- Making functional nodes or clusters demands third-party tools.
- Support is available for three years after that you need to pay for the support.