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!
What is a Database System?
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.
How Do Database Systems Work?
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.
Different Database System Types
Centralized Database Systems
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.
Pros of Centralized Database Systems
- Integrity: A centralized system ensures there's only one copy of each piece of data in the database. That reduces data redundancy and inconsistency and enhances data reliability.
- Security: It can protect the data from unauthorized access, modification, or deletion by using authentication, encryption, and other mechanisms.
Cons of Centralized Database Systems
- Accessibility: This system relies on network speed and availability to have real-time access to the data. Network failures or congestion cause delays or errors in data processing.
- Availability: A centralized database system relies on the server's uptime and performance to provide access to the data. If there is a server failure or downtime, database administrators may be unable to access data.
Distributed Database Systems
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.
Pros of Distributed Database Systems
- Performance: A distributed database system can improve performance by spreading the workload among multiple nodes. That reduces the load on each node and increases the throughput and response time.
- Availability: It can boost availability by replicating data across multiple nodes. That ensures that if one node fails or becomes inaccessible, another node can provide access to the same data.
Cons of Distributed Database Systems
- Cost: This system requires more hardware and software than other database systems. The cost of distributing the data is significantly higher.
- Complexity: Distributed database systems require more resources for their design, implementation, maintenance, and troubleshooting. Additionally, challenges arise from network and node failures, data consistency, and distributed recovery.
Relational Database Systems
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.
Pros of Relational Database Systems
- Integrity: Relational database models ensure accurate and consistent data across all tables. They use constraints, such as primary keys, foreign keys, and check controls, to prevent data duplication, inconsistency, and errors.
- Portability: They ease transferring or migrating data from one location to another with standardized formats and logical structures.
Cons of Relational Database Systems
- Access: These depend on the network speed and availability for real-time data access. If there is a network failure, users may experience delays or errors in accessing or processing the data.
- Diversity: The systems may be unable to accommodate types or formats that require extra storage or processing methods. It may need modifying or integrating multiple databases to support diverse data sources or applications.
Object-Oriented Database Systems
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.
Pros of Object-Oriented Database Systems
- Modeling: Object-oriented systems can model complex and diverse data types more easily than other types. They can also support user-defined types and methods that extend the system's functionality.
- Manipulation: These databases offer efficient and effective data manipulation, performing complex operations on objects without requiring multiple tables or records.
Cons of Object-Oriented Database Systems
- Administration: They may have more difficulty or overhead than other systems in managing and maintaining the data. They may also lack standardization or support for common features or functions, such as views, triggers, stored procedures, etc.
- Access: These systems may have lower performance or compatibility than others when accessing data through standard interfaces or tools. They may also require more network bandwidth or resources to transfer complex objects across nodes or sites.
NoSQL Database Systems
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.
Pros of NoSQL Database Systems
- Performance: NoSQL database systems can provide faster and more consistent performance than other systems. They can use caching, indexing, or replication techniques to optimize data access and processing.
- Integration: They can integrate data more seamlessly with object-oriented programming languages than other systems. They can use the same model and concepts as the programming languages, reducing their impedance mismatch.
Cons of NoSQL Database Systems
- Oversight: These may have more difficulty or overhead than other systems in managing and maintaining the data. They may also lack standardization or support for common features or functions, such as views, triggers, stored procedures, etc.
- Admission: NoSQL database systems may have lower performance or compatibility than others when accessing data. They may also require more network bandwidth or resources to transfer complex objects across nodes or sites.
How To Choose a Database System?
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.
Database System Models
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!
Database System Performance
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.
Database System Scalability
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.
Database System Security
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.
Database System Costs
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).
Conclusion
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!
