Ever wondered how big tech companies store and manage your online profiles? Or how banks manage your finances and credentials?
They do it all through databases.
A database is an organized collection of data that can be easily accessed and managed. All the companies in the world, big or small, use databases to keep and manage their records, whatever they may be related to.
However, there isn't only one kind of data or one way to manage them. This means there isn't only one type of database.
Here, we will discuss the different types of databases and briefly explain how they work.
Types of Databases and How They Work
There are primarily two types of databases — relational databases and non-relational databases.
Relational databases are databases that organize data into tables. There are rows and columns where information is stored.
Each table represents a specific data type, and each row represents a unique record.
These tables are linked, hence the 'relational' moniker. They are connected through common fields.
This makes retrieving and combining data from multiple tables using queries easier. SQL (Structured Query Language) and database management systems like MySQL, Oracle, PostgreSQL, etc., are used to access data from them.
Here's an illustration to help you understand better:
Suppose this is a grocery store's database. Here, 'Customers' is a table within the database.
The first row is the attributes of the table. The remaining rows have customer data.
Then, imagine we have another table named 'Products,' which contains customer order details. Here's how the two tables would be linked:
Relational databases are used in banking, inventory management, and e-commerce. They are designed to hold large amounts of structured data and enable ease and flexibility in their storage and access.
Opposite to relational databases, non-relational databases are databases that do not organize data in tables. They are more flexible and dynamic in the ways they store information.
They use key-value pairs, documents, graphs, and other data models to organize large volumes of unstructured and semi-structured data. These include social media posts, sensor data, etc.
Another feature of this database is its speed and scalability. Non-relational databases are used in web applications, big data analytics, and real-time systems where speed and flexibility are crucial.
We use non-relational database management systems (Non-RDBMS) like MongoDB, Redis, etc. to access these databases.
This illustration will aid your understanding:
Here, the customers' data are stored in key-value pairs. The two records are not related to each other.
In-depth: SQL vs. NoSQL: Which Database Should You Use?
Other than these, there are a few other types of databases that are neither relational nor non-relational. They are:
Similar to object-oriented programming, object-oriented databases store data in the form of objects and classes. They can use either relational or non-relational models.
Hierarchical databases organize data into a tree-like structure. The nodes represent a record, and its children (branches) represent its attributes. This database model isn't common today; they are primarily used in mainframes.
Time-series databases are databases that store and analyze large amounts of time-stamped data like sensor readings and financial data. They are optimized for time-based queries and analysis.
Spatial databases store and manage data such as maps, geographical information, and satellite imagery, i.e., spatial data. They have specialized structures and algorithms to perform spatial queries and analyses.
What are the two most frequently used types of databases?
Relational/Sequence Database and Non-relational/Non-sequence databases are the two most frequently used types of databases.
How do I choose a database?
While choosing a database, consider these five things — your storage needs; the scalability of the database; availability of support and documentation; integration with other technologies; and the cost of the database.
Which is the fastest database?
There is no one answer to this question. Different databases are faster in different use cases and scales. Many factors affect the speed of a database, such as its engineering and architecture, the hardware it's running on, the volume of data within it, the database admin's skill levels, etc.
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