Non-Relational Databases, also known as NoSQL Databases, provide the necessary mechanism to store and retrieve data in formats anything but tabular relations. A non-relational database uses a storage model tailored to the data that we hold. Although these types of databases have been around since the 1960s, the term No-SQL only became popular in the late 1990s and early 2000s.
The majority of non-relational databases are embedded in websites such as Google, Yahoo!, Amazon, and Facebook. These websites introduce a slew of new applications every single day, and they have millions and millions of users, so existing RDBMS solutions are generally unable to handle sudden spikes, which can cost businesses their hard-earned business.
In this blog, you will gain new insights into Non-Relational Database Management Systems. We’ll be discussing the key features of the non-relational database management system. Let’s begin.
Table of Contents
What is Relational Database Management System?
Image Source
E.F. Codd of IBM coined the term Relational Database in the 1970s, and in 1974 Donald D. Chamberlin and Raymond F. Boyce released SQL, or Standard Query Language, which allows the user to interact with the Relational Database Management System.
A Relational Database Management System stores data in tables that contain specific pieces and types of data. A store, for example, could keep track of their customers’ names and addresses on one table and their orders on another. This type of data storage is commonly referred to as structured data.
Structured Query Language is used in Relational Database Management System (SQL). The Database in a Relational Database design typically contains tables made up of columns and rows. When new data is entered, it is inserted into existing tables or new tables are created. Then, relationships can be formed between two or more tables.
Image Source
A Relational Database, as previously defined, is made up of tables, and each table is made up of rows and columns. Each table has a special column called the primary key that contains only distinct and unique values. The primary key defines the relationship between the tables.
Hevo Data, a No-code Data Pipeline helps to integrate or replicate data from Relational or NoSQL Databases (among 100+ integrations) of your choice to make your data integrations easier. Hevo is fully-managed and completely automates the process of not only loading data from your desired database but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code.
Get started with hevo for free
Hevo is the fastest, easiest, and most reliable data replication platform that will save your engineering bandwidth and time multifold.
Try our 14-day full access free trial today to experience an entirely automated hassle-free Data Replication!
What is Non-Relational Database Management System?
Image Source
Non-Relational Databases, also known as No-SQL databases, are those that do not require any tables, fields, or records. Although this type of database has existed since the 1960s, the term No-SQL was coined in the late 1990s and early 2000s.
NoSQL Databases are not the same as SQL Databases and operate in a different manner. It must handle semi-structured or unstructured data. It is made up of files in various folders rather than tables. They can store any type of data, including JSON, XML, and others. As a result, creating and managing data in NoSQL is simpler and faster.
A Non-Relational Database Management System is frequently used to organize large amounts of complex and diverse data. A large store, for example, might have a database where each customer has their own document containing all of their information, from name and address to order history and credit card information. Despite their different formats, all of this information can be stored in the same document.
Non-Relational Database Management Systems are often faster than Relational Databases since a query does not have to look at numerous tables to acquire a response, as relational Databases frequently do. Non-Relational Databases are thus suited for storing regularly changing data or for applications that work with a variety of data types. They can be used to support rapidly developing applications that require a dynamic database that can change quickly and accommodate large amounts of complex, unstructured data.
Key Features of Non-Relational Database Management System
Below are a few notable features of the Non-Relational Database Management System:
- Multiple Data Model Support: Whereas Relational Databases require data to be placed in tables and columns in order to be accessed and analyzed, the various data model capabilities of NoSQL databases allow them to be extremely flexible when it comes to data handling.
- Peer-to-Peer architecture allows for Easy Scaling: Relational Databases can’t scale because they’re built with a traditional master-slave architecture, which means scaling UP via bigger and bigger hardware servers rather than scaling OUT or worse via sharding.
- Flexibility: Whereas Relational Databases require data to be placed in tables and columns in order to be accessed and analyzed, NoSQL Databases’ multi-model capabilities make them extremely flexible when it comes to data handling.
- Capabilities for Distribution: Look for a NoSQL database that is designed to distribute data on a global scale, which means it can write and read data from multiple data centers and/or cloud regions.
- There is no Downtime: The final but not least important key feature to look for in a NoSQL Database is zero downtime. A Masterless Architecture enables this by allowing multiple copies of data to be maintained across different nodes.
Relational vs Non-Relational Database Management Systems: Key Differences
The table below summarises the differences between Relational and Non-Relational Database Management Systems.
| Sl.no | Relational Database Management System | Non-Relational Database Management System |
| 1 | SQL Databases are what they’re called. | They are known as NoSQL Databases. |
| 2 | They first appeared in the 1970s. | They first appeared in the 1960s. |
| 3 | Tables are used to store data. | Data is classified as either structured or unstructured. |
| 4 | It will almost certainly have a larger server to accommodate a large amount of data. | NoSQL Databases do not require the purchase of a larger server to manage data; instead, they can scale horizontally. |
| 5 | Data access is slower. | Accessing data faster than a relational database. |
| 6 | Examples include MySQL, Oracle, MariaDB, and SQLite. | Examples include MongoDB, Neo4j, and Redis. |
Providing a high-quality ETL solution can be a difficult task if you have a large volume of data. Hevo’s automated, No-code platform empowers you with everything you need to have for a smooth data replication experience.
Check out what makes Hevo amazing:
- Fully Managed: Hevo requires no management and maintenance as it is a fully automated platform.
- Data Transformation: Hevo provides a simple interface to perfect, modify, and enrich the data you want to transfer.
- Faster Insight Generation: Hevo offers near real-time data replication so you have access to real-time insight generation and faster decision making.
- Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
- Scalable Infrastructure: Hevo has in-built integrations for 100+ sources (with 40+ free sources) that can help you scale your data infrastructure as required.
- Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
TRY OUR 14 DAY FREE TRIAL
Case Studies for Relational and Non-Relational Database Management System
All types of Databases can be used for a wide range of projects; there is no hard and fast rule that one should be preferred over the other. However, you can make an informed decision if you first analyze certain aspects of your project.
1) Use Case for Relational Database Management System
- Safe Environment: Relational Databases require more time to set up and manage, but they provide data Atomicity, Consistency, Isolation, and Durability, also known as ACID. It is an excellent choice for projects in finance, healthcare, and e-commerce. ACID principles can be applied to any project that involves financial transactions or sensitive data.
- Solid data Structure: A relational database will provide a stable, secure environment for data management if your project requirements do not include constant changes, in-app functionality, and processing algorithms. The lack of SQL flexibility will be less noticeable because your application does not require it.
- Budgeting: Generally, finding a SQL development team is less expensive because there are more qualified specialists to choose from. All SQL tools adhere to the same principles, whereas non-relational database functionality is tool-specific.
2) Use Case for Non-Relational Database Management System
- Timing: No-SQL databases are easier to set up and require a less methodical approach to data entry. You can insert unstructured data into the document, assign it a key, and deal with the organization later. It’s an excellent idea for MVP development and time-sensitive software releases.
- A Large Amount of Unstructured Data: If you’re developing a social media app or a community marketplace, you’ll need a tool that can store the personal information of millions of users. Because much of this data will be unstructured (profile descriptions, Feed updates, etc.), the traditional column-row model will be more difficult to set up and run.
These are obviously broad distinctions; in reality, each rule has exceptions. However, if you value stability over flexibility, SQL-based systems are the way to go. Non-relational databases, on the other hand, are your best bet if you deal with large amounts of unstructured data.
Benefits of Non-Relational Database Management System
Today’s applications collect and store massive amounts of increasingly complex customer and user data. Of course, the value of this data to businesses is in its analytical potential. Using a Non-Relational Database Management System can reveal patterns and value even in massive amounts of disparate data.
Non-Relational Database Management System has several advantages, including:
- Organization of Massive Datasets: Non-Relational Databases, in the age of Big Data, can not only store massive amounts of information, but they can also query these datasets with ease. Non-Relational Databases have significant advantages in terms of scale and speed.
- Database Expansion that is Adaptable: Data is not fixed. As more data is collected, a Non-Relational Database Management System can absorb these new data points, enriching the existing database with new levels of granularity even if they do not fit the data types of previously existing data.
- Several Data Structures: Users’ data is now collected in a variety of formats, ranging from numbers and strings to photo and video content and message histories. A Non-Relational Database Management System can combine different types of information in the same document regardless of the format in which it is stored.
- Designed for the Cloud: A Non-Relational Database Management System can be extremely large. Because they can grow exponentially in some cases, they require a hosting environment that can grow and expand with them. Because of its inherent Scalability, the cloud is an ideal home for non-relational databases.
Limitations of Non-Relational Database Management System
The Limitations of the Non-Relational Database Management System are as follows:
- ACID: Because they are BASE, NoSQL does not guarantee ACID transactions.
- Backup: The disadvantage of Non-Relational Databases is that they do not have a backup. MongoDB has some backup tools, but they are inadequate. Finally, NoSQL databases are not mature enough to receive adequate backup.
- Standard Operating Procedures for NoSQL Databases: Databases have no standardized rules. Because the design and query language differ from one NoSQL database to the next, there is no standard process for accessing the data, whereas there are some common ways to access the data in Relational databases.
Conclusion
Applications must be able to efficiently query data and deliver results almost instantly. Non-Relational Database Management System is an obvious choice for this type of setting. They provide both Security and Agility, allowing for rapid application development in an Agile Environment. They are easier to manage and less complex than Relational Databases, and they can result in lower Data Management costs while providing Superior Performance and Speed.
To become more efficient in handling your Databases, it is preferable to integrate them with a solution that can carry out Data Integration and Management procedures for you without much ado and that is where Hevo Data, a Cloud-based ETL Tool, comes in. Hevo Data supports 100+ Data Sources and helps you transfer your data from these sources to Data Warehouses in a matter of minutes, all without writing any code!
Visit our Website to Explore Hevo
Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. Hevo offers plans & pricing for different use cases and business needs, check them out!
Share your experience of learning the Non-Relational Database Management System in the comments section below!