A database is a collection of data stored in an orderly manner. To run a system efficiently, you’d need an effective memory of the past and present records that went into and/or came out of that particular system. The same applies to a business or organization that would require the cooperative efforts of a number of individuals. For this purpose, companies, large and small, and organizations like hospitals, schools, and universities utilize a very useful method of acquiring, assembling, and sharing the data in systematic ‘entities’ that are stored within different types of databases available. These different types of databases have various structure types to suit the unique needs of an organization.
The blog gives an overview of DBMS, explains what are databases, the types of databases, what are databases used for, specifically what are databases used for in business, and discusses the common types of database structures.
Definition of Database
The database is “a structured set of data held in a computer, especially one that is accessible in various ways.” However, there are various types of databases, each providing different functionality to their users. For example, No SQL database offers high scalability to its users while relational database schemas are stricter in nature and provide more consistency and structure.
Types of Database Objects
There are four different types of database objects that help users to compile, enter, store, and analyze important data:
What Are Databases Used For?
Databases are used for keeping the mountains of data collected in an orderly manner and easily accessible to an authorized user. Different databases are used by companies depending on the nature of their data. They can be important for a business’s growth in numerous ways:
- Allows a business to make more informed business decisions.
- Efficiently store and retrieve related information.
- Helps analyze and aggravate business data.
- Collect and store crucial customer data from different applications.
- Delivers data-driven timely, personalized applications, and real-time analytics.
- Ensures accurate, reliable, and immediate access to crucial business data that can be used by different business departments to comprehend data patterns, generate reports, predict future trends.
- Often data is mapped through hierarchical databases used by legacy systems to relational databases used in the data warehouses.
Types of Database Structures Explained
The type of database a company uses should be aligned with the company’s requirements and needs. There are various types of database structures:
- Hierarchical database: The hierarchical database follows a ranking order or a parent-child relationship to structure the data.
- Network database: The network database is similar to the hierarchical database but with some changes. The network database allows the child record to connect with various parent records, therefore, allowing two-directional relationships.
- Object-Oriented database: In the object-oriented database, the information is stored in an object-like manner.
- Relational database: A relational database is table-oriented where every bit of data has a link with every other bit of data.
- Non-relational or NoSQL database: A no SQL database uses a variety of formats, such as documents, graphs, wide columns, etc, which offers great flexibility and scalability to a database design.
However, databases are widely divided into two major types or categories, namely, Relational or Sequence Databases and Non-relational or Non-sequence databases or No SQL database. These may be used by an organization individually or combined, depending on the nature of the data and the functionality required.
Let’s delve into the various types of databases mentioned above.
People often ask, what is the most common type of database? A relational database is an answer to their question. This type of database management system (DBMS) uses schema, which is a template used to dictate the structure of data that will be stored within the database.
Like for a company selling products to its customers, it is essential for them to have some form of stored knowledge as to where did these products go, to whom, and in what quantity.
There may be different tables used for each approach and even relational database table types. For example, one table can be used to show the basic information of the customers, a second, used for the information of the products that are sold and a third table can be used to enumerate who purchased this product, how many times and where.
There are keys associated with the tables in a relational database. They help in providing a quick database summary or access to the particular row or column that you might want to check.
The tables, which are also called entities, are all in relation to each other. The table with the information about customers might provide a specific ID to each customer that can simply denote all there is to know about that customer like their address, name, and contact information. Also, the table with the product description can assign a particular ID to each product. The table where all the orders are recorded would just need to record these IDs and their quantity. Any change in any one of these tables will affect all of them but in a predictable and systematic manner.
Data integrity is ensured by constraints of the Relational Database Management Systems (RDBMS). An RDBMS ensures that the data that shows up is accurate and can be relied upon. However, there are different relational database types. The different SQL database types are Microsoft SQL Server, Oracle Database, MySQL, and IBM DB2. Today, MySQL is one of the most popular and widely used types of SQL database.
There are different types of SQL databases. Some examples of these Structured Query Language (SQL) databases are:
Oracle database system, an Oracle Corporation product, serves as a multimodal management system.
Also called Postgre, PostgreSQL emphasizes standard compliance along with extensibility and serves as an object-relational database management system.
This particular open-source RDBMS runs on all the available platforms, like, Windows, Linux, and UNIX.
A product of Microsoft, SQL Server is mainly used to store and retrieve data to and from software application systems.
Merits and Demerits of Relational Databases
Relational databases have their own merits and demerits that are worth considering before opting to invest in them:
- Relational databases follow are a strict schema, meaning that each new entry must have different components that make it fit in that preformed template. This enables the data to be predictable and easily assessable.
- ACID-compliance is a must for all RDBMS databases. This means that they must ensure the provision of Atomicity, Consistency, Isolation, and Durability.
- They are well structured and give little to no space for any kind of error to occur.
- The meticulous nature, strict schemas, and constraints of relational databases make it nearly impossible to be stored in the numbers that are a requirement for today’s mammoth internet data.
- It’s impossible to scale horizontally as relational databases follow a particular schema. Although vertical scaling seems like the obvious answer, it’s not. Vertical scaling has a limit and, in this time, and age, the data collected via the internet daily is simply too large to imagine that vertical scaling would work for long.
- Schema constraints also impede the migration of data to and from different RDBMS. They need to be identical or it will not simply work.
This non-relational form of database organization is more forgiving in its structure and form than relational databases. Instead of tables with columns and rows, they have collections of different categories like users and orders, for example. These collections are illustrated by documents. So, there can be multiple documents in one collection and they can or cannot follow any particular pattern or schema.
A document can have a name, address, and product in a collection; at the same time, another document can have just a name and product in the same collection as there is no particular schema to these documents. Also, different collections might not necessarily have relations among them.
The different types of non-relational databases are:
This type only stores and provides quick and simple knowledge regarding key-value pairs. This is a simple and easy way to store and access the data. Some examples are Amazon DynamoDB and Redis.
Wide Column Stores
This type can be also called a multidimensional key-value store as it stores and manages humongous amounts of data in tables or multiple columns, each column of which can act as a record. This helps in the scaling of multiple petabytes of data. Notable examples are Scylla, HBase, and Cassandra.
Here, the uniform structure is not a necessity for records to have. They can have a wide array of types and values and all of them can be nested. The data gets stored in JSON documents, and these documents resemble those of key-value and wide-column. Some of the most famous NoSQL databases fall into this category, namely, Couchbase and MongoDB.
They are distinguished from document stores in a way that they help in making the data available by simple text-based searches. Some examples are Solr, Splunk, and Exasticsearch.
Graph databases show the connections between different data points. They are used mostly when there is a requirement of analyzing different types of data and their relationship with each other. These are represented in the form of a network of objects or nodes that are related. Examples are the Datastax Enterprise Graph and Neo4J.
Merits and Demerits of Non-Relational Databases
Like everything else, non-relational databases are not perfect and have some advantages but also some limitations. These include:
- Their schema-free nature makes it easier to manage and store huge volumes of data. They can also be easily scaled horizontally.
- Data is not too complex and can be distributed among a number of distinguished nodes for better accessibility.
- Since they have no specific structure or schema for the data stored, you cannot rely on your data for a certain field because it might not have it.
- Having no relations makes it very hard to update the data as you will have to update every single detail separately.
Types of Database Users
There are various types of database (DBMS) users, such as:
- Database Administrator (DBA)
- System Analyst
- Application Programmer
- Database Designer