Data is everywhere! You create and consume data daily, from social media posts to online transactions.
But how do you store, manage, and retrieve data efficiently and effectively? You need database systems.
These software applications help you create, manipulate, and query data in a structured and organized way.
However, not all database systems are the same.
There are different database systems, each with its features, benefits and drawbacks.
In this blog post, you’ll learn about the main kinds of databases and how to use these systems for various purposes!
You may have heard the term "database" before, but do you know what it means?
A database is not just a fancy word for a spreadsheet or a file folder. A
database is an organized collection of data or information that a computer can store, access, and manipulate.
There are different types according to how you organize data.
For example, in navigational databases, the data is shown as a tree-like structure (hierarchical databases). This capability makes it more flexible and have multiple and complex relationships between them (network databases).
There are also cloud databases where data is on a cloud rather than a local server. As a result, cloud databases are great for enterprise databases where many people need access to the data.
If a small group of people or just one person is going to manage the data, they can use a personal database.
Sounds simple enough? Wait, there's more!
A database is not just a bunch of data. It also needs a way to manage that data.
That's where the different types of database management systems come in.
A database system, also known as a Database Management System (DBMS) handles the interactions between users, applications and databases.
The DBMS allows you to create, update, delete and query data in the database using a Structured Query Languages.
Database systems also handles security, performance, backup and recovery.
You may be wondering how database systems work: how do DBMS store and retrieve data quickly and efficiently?
How do they handle complex queries and operations on the data?
Well, a DBMS has three main components: the internal, the conceptual and the external level.
The internal level represents how data gets physically stored in the entire database.
It deals with data internal structures, file formats, indexes and hashing.
This level also encloses compression, encryption and other techniques to optimize storage and access.
The DBMS manages the inner level.
The database organizes and represents the data at the conceptual level.
This layer defines the logical schema, which includes tables, columns, keys and constraints.
Other edges include relationships, and other elements that describe the data model.
It provides a common view of the data for all users.
The external level represents how users and applications see and use the data.
It defines multiple views or subsets of the data for specific purposes or contexts.
It allows users to access only the necessary data without exposing unnecessary details.
Here, all data is stored and managed in a single unit, whether a computer, a server or a mainframe.
The unit that keeps the data is called the server, and the computers or devices that access the data are called the clients.
Clients communicate with the server through a network, such as a Local Area Network (LAN) or a Wide Area Network (WAN).
The server handles all client requests and performs data operations like creating, updating, deleting and querying.
The server also manages the data's security, performance, backup, and recovery.
In a distributed database system, the data is stored and managed on multiple units (computers, servers or mainframes.)
The unit that keeps the data is called a node, and the network of nodes is called a cluster.
The nodes communicate with each other through the network to exchange data and coordinate operations.
Each node can run its DBMS, which provides the functionalities.
Relational systems are among the most popular ones to store and manage data in a series of tables.
Tables consist of rows and column-oriented databases. Each row represents a record and each column represents an attribute.
What's more, tables can link to each other using keys and unique identifiers that establish the relationships among data.
Object-oriented databases store and manipulate data as objects rather than tables or records.
Here, objects are entities with data and behavior, and the user or the programming language can define them.
They use the same model and concepts as object-oriented programming languages.
Some edges enclose classes, inheritance, polymorphism, encapsulation and abstraction.
Object-Oriented DBMS can work with complex and diverse data types such as Artificial Intelligence applications.
NoSQL or non-relational databases store data in various formats, such as documents, key-value pairs, graphs, or columns.
Unlike Relational Database Management Systems (RDBMSs), these databases use different models to represent and manipulate data.
Document databases store data as JSON or XML and key-value databases store data as simple key-value pairs.
Graph databases store data as nodes and edges, and so on.
There are many factors to consider when choosing a database system!
There's also performance and scalability requirements, security and reliability, development and maintenance costs and compatibility and integration.
The data model defines how the data is structured, organized, and manipulated in the database.
Database systems support different data models, such as relational, hierarchical structures, networks, documents, key-value stores, graphs, etc.
The data model affects how easy or difficult it is to store and query your data and how flexible or rigid your schema is.
Choose a data model that matches your data's shape, complexity and query patterns!
Performance requirements depend on factors like hardware resources, network latency and data size and distribution.
Other edges include indexing and caching strategies, as well as the concurrency and locking mechanisms.
You should choose a database system that can meet your performance expectations and Service Level Agreements (SLAs)!
Also, consider how each handles peak loads and spikes in traffic.
DBMS have different scalability models and architectures, such as master-slave, master-master, sharing, replication, etc.
Pick a database system that can scale with your needs, budget, availability and fault tolerance.
Security refers to how well the database can protect your data from unauthorized access, modification or deletion.
It also involves authentication, authorization, encryption, auditing, backup, recovery, etc.
Select a system that meet your security standards and prevent common threats such as SQL injections and data breaches.
Cost includes many components: license fees, hardware expenses, Cloud Services fees, personnel salaries, training costs, support contracts, etc.
You should choose a database system that fits your budget and provides a good Return On Investment (ROI).
Database systems are Business Intelligence -based applications that can help you manage and manipulate data organizationally.
When deciding on a database system, thee is no one-size-fits-all solution!
You should consider aspects like data model, performance, scalability, security and cost.
You may also have to use more than a single database type system for a wide range of purposes.
Think of even combining them in a hybrid or polyglot approach according to your requirements!
Data is everywhere! You create and consume data daily, from social media posts to online transactions.
But how do you store, manage, and retrieve data efficiently and effectively? You need database systems.
These software applications help you create, manipulate, and query data in a structured and organized way.
However, not all database systems are the same.
There are different database systems, each with its features, benefits and drawbacks.
In this blog post, you’ll learn about the main kinds of databases and how to use these systems for various purposes!
You may have heard the term "database" before, but do you know what it means?
A database is not just a fancy word for a spreadsheet or a file folder. A
database is an organized collection of data or information that a computer can store, access, and manipulate.
There are different types according to how you organize data.
For example, in navigational databases, the data is shown as a tree-like structure (hierarchical databases). This capability makes it more flexible and have multiple and complex relationships between them (network databases).
There are also cloud databases where data is on a cloud rather than a local server. As a result, cloud databases are great for enterprise databases where many people need access to the data.
If a small group of people or just one person is going to manage the data, they can use a personal database.
Sounds simple enough? Wait, there's more!
A database is not just a bunch of data. It also needs a way to manage that data.
That's where the different types of database management systems come in.
A database system, also known as a Database Management System (DBMS) handles the interactions between users, applications and databases.
The DBMS allows you to create, update, delete and query data in the database using a Structured Query Languages.
Database systems also handles security, performance, backup and recovery.
You may be wondering how database systems work: how do DBMS store and retrieve data quickly and efficiently?
How do they handle complex queries and operations on the data?
Well, a DBMS has three main components: the internal, the conceptual and the external level.
The internal level represents how data gets physically stored in the entire database.
It deals with data internal structures, file formats, indexes and hashing.
This level also encloses compression, encryption and other techniques to optimize storage and access.
The DBMS manages the inner level.
The database organizes and represents the data at the conceptual level.
This layer defines the logical schema, which includes tables, columns, keys and constraints.
Other edges include relationships, and other elements that describe the data model.
It provides a common view of the data for all users.
The external level represents how users and applications see and use the data.
It defines multiple views or subsets of the data for specific purposes or contexts.
It allows users to access only the necessary data without exposing unnecessary details.
Here, all data is stored and managed in a single unit, whether a computer, a server or a mainframe.
The unit that keeps the data is called the server, and the computers or devices that access the data are called the clients.
Clients communicate with the server through a network, such as a Local Area Network (LAN) or a Wide Area Network (WAN).
The server handles all client requests and performs data operations like creating, updating, deleting and querying.
The server also manages the data's security, performance, backup, and recovery.
In a distributed database system, the data is stored and managed on multiple units (computers, servers or mainframes.)
The unit that keeps the data is called a node, and the network of nodes is called a cluster.
The nodes communicate with each other through the network to exchange data and coordinate operations.
Each node can run its DBMS, which provides the functionalities.
Relational systems are among the most popular ones to store and manage data in a series of tables.
Tables consist of rows and column-oriented databases. Each row represents a record and each column represents an attribute.
What's more, tables can link to each other using keys and unique identifiers that establish the relationships among data.
Object-oriented databases store and manipulate data as objects rather than tables or records.
Here, objects are entities with data and behavior, and the user or the programming language can define them.
They use the same model and concepts as object-oriented programming languages.
Some edges enclose classes, inheritance, polymorphism, encapsulation and abstraction.
Object-Oriented DBMS can work with complex and diverse data types such as Artificial Intelligence applications.
NoSQL or non-relational databases store data in various formats, such as documents, key-value pairs, graphs, or columns.
Unlike Relational Database Management Systems (RDBMSs), these databases use different models to represent and manipulate data.
Document databases store data as JSON or XML and key-value databases store data as simple key-value pairs.
Graph databases store data as nodes and edges, and so on.
There are many factors to consider when choosing a database system!
There's also performance and scalability requirements, security and reliability, development and maintenance costs and compatibility and integration.
The data model defines how the data is structured, organized, and manipulated in the database.
Database systems support different data models, such as relational, hierarchical structures, networks, documents, key-value stores, graphs, etc.
The data model affects how easy or difficult it is to store and query your data and how flexible or rigid your schema is.
Choose a data model that matches your data's shape, complexity and query patterns!
Performance requirements depend on factors like hardware resources, network latency and data size and distribution.
Other edges include indexing and caching strategies, as well as the concurrency and locking mechanisms.
You should choose a database system that can meet your performance expectations and Service Level Agreements (SLAs)!
Also, consider how each handles peak loads and spikes in traffic.
DBMS have different scalability models and architectures, such as master-slave, master-master, sharing, replication, etc.
Pick a database system that can scale with your needs, budget, availability and fault tolerance.
Security refers to how well the database can protect your data from unauthorized access, modification or deletion.
It also involves authentication, authorization, encryption, auditing, backup, recovery, etc.
Select a system that meet your security standards and prevent common threats such as SQL injections and data breaches.
Cost includes many components: license fees, hardware expenses, Cloud Services fees, personnel salaries, training costs, support contracts, etc.
You should choose a database system that fits your budget and provides a good Return On Investment (ROI).
Database systems are Business Intelligence -based applications that can help you manage and manipulate data organizationally.
When deciding on a database system, thee is no one-size-fits-all solution!
You should consider aspects like data model, performance, scalability, security and cost.
You may also have to use more than a single database type system for a wide range of purposes.
Think of even combining them in a hybrid or polyglot approach according to your requirements!
