What is DBMS or RDBMS?
DBMS (Database Management System) and RDBMS(Relational Database Management System) are both types of computer software designed to capture, manage and analyze a large set of databases.
DBMS stores data in a file while RDBMS uses tables or a relational schema for storage, maintenance and management.
Why is DBMS or RDBMS Required?
Data is the oil for the smooth growth of the company. Its significance lies in the details, the information acquired from it, the decisions made based on the data.
Every organization and industry needs a space to store this data and maintain it for several purposes.
Databases provide the space to store a large collection of data electronically. To capture, manage and analyze that data, organizations require an automatic system. This is where the need for RDBMS and DBMS arises.
You can see examples of the requirement for RDBMS and DBMS in your everyday life.
From your OTT platform recommendations to companies’ new decisions based on customer data, it is all possible through the storing, manipulation and maintenance of data.
For example, Facebook runs a campaign to test the new ads feature on FB stories. It requires a system to collect the data, arrange it, and maintain it securely for analysis.
Therefore, the type of data whether structured or unstructured can be stored, recorded, updated, deleted and manipulated on a database management system.
What is SQL?
SQL or the Structured Query Language is the most common and popular programming language for the relational database management system. It is a language designed to extract, store, insert, delete, update and manage data for structured data and strategic analysis.
SQL is widely used by top tech companies like Facebook, Whatsapp, etc for data processing solutions. It is used for different types of RDBMS including Oracle, MySQL, SQLServer, etc.
Functions of SQL:
- Perform queries on the database
- Database Retrieval
- Set permissions on tables, views
- Can insert records into the database
- Update records in a database
- Delete records from a database
- Create new databases, or new tables in a database
- Create stored procedures & views in a database
What is NoSQL?
NoSQL database provides a mechanism for storage and retrieval of data that is modelled other than tabular form. It was introduced by Carl Stroz in the year 1998 called a Non-relational database. Now, it stands for Not only SQL. It is not limited to storing data in tables, instead, enables the big data to be stored in the structured, unstructured, semi-structured or polymorphic form.
It is not limited to storing data in tables, instead, enables the big data to be stored in the structured, unstructured, semi-structured or polymorphic form.
Companies like Twitter and Google, with a tremendous amount of data set like the user data of the social platforms, prefer to use NoSQL over any other RDBMS.
Features of SQL
- Provide High-Performance Capabilities
- SQL is a powerful tool as it is highly compatible with all types of RDBMS like MySQL, SQL Server, Oracle Database, MS Access, etc.
- Data Consistency: SQL adheres to ACID properties with a strict schema that ensures better data consistency.
- Ensures Vertical Scalability
- Handle Large Transactions with efficiency
- Robust Security Measures like rigid schema, data consistency, data integrity, regular updates, etc.
- Suitable for every type of organization – large or small.
- SQL is easy to learn and manage
- Open Source Programming Language
- Supports Data Definition Language and Data Manipulation Language to query the databases
Features of NoSQL
- NoSQL has higher scalability than other database management systems
- Schema Free: You do not need to define the schema of the database before storing the data onto the system.
- NoSQL allows the distribution of data on more than just one device.
- With NoSQL Database, you do not require specialized or complex hardware or storage solutions.
- Does not require data normalization
- Simple API for easy user interfaces
- Can store unstructured, semi-structured, or structured data.
SQL vs NoSQL: Head to Head Comparison
|Define||SQL databases are a type of system software that supports management, analysis, capturing and querying the structured data in a relational format.||NoSQL databases are a type of software that allows to maintain and retrieve structured, unstructured, polymorphic data for different purposes.|
|Purpose||A language used to communicate with databases for storage, deletion, updation, insertion and retrieval of data.||A software to retrieve, store and manage scalability of databases.|
|Development Year||SQL was developed in the year 1970 for flat file storage problems.||NoSQL was developed in 2000 as an enhanced version for SQL databases for unstructured and semi-structured data.|
|Query Language||SQL databases support Structured Query Languages.||NonSQL does not have any declarative query language.|
|Type||Supports table based data type.||Supports document oriented, graph databases, key value pair-based.|
|Scalability||Vertically Scalable (Add resources to increase the capacity of the existing hardware and software).||Horizontally Scalable (Changing small nodes with larger nodes to increase the capacity of the existing hardware and software).|
|Schemas||SQL supports predefined schemas, making the storage of data restrictive to structured type only.||Nosql supports dynamic schemas to store different forms of data.|
|Architecture||SQL is relational.||Non-SQL is non relational.|
|Ideal Use Cases||SQL is best suitable for complex queries, multi-row transactions.||NoSQL is best suited for unstructured data or documents. Not ideal for complex queries.|
|Hardware||Databases that support SQL require powerful hardware to support vertical scaling.||NonSQL databases require commodity hardware for horizontal scaling.|
|Properties||SQL enables ACID(atomicity, consistency, isolation, and durability) properties||NonSQL follows CAP (consistency, availability, partition tolerance) properties.|
|Data Storage||SQL does not support hierarchical storage of data.||NoSQL is best suited for hierarchical storage of data.|
|Distributed Data||SQL databases can only be run on a single system and hence, does not follow distribution of data.||NoSQL databases are designed to follow data distribution features like repetition, partition.|
|Best Features||• Secure|
• Cross Platform Support
|• High Performance|
• Easy to use
|Top Companies Using||Microsoft, Dell, Cognizant, etc.||Amazon, Capgemini, Adobe, etc.|
|Examples||SQL supports databases like MySQL, SQL Server, Oracle, etc.||Nosql databases are Hbase, MongoDB, Redis, etc.|
In order to get a clear picture of which one is better, we need to look at the advantages and disadvantages of SQL and NoSQL.
Here are the pros and cons of SQL and NoSQL.
Pros and Cons of SQL and NoSQL
To understand the clear difference between SQL and NoSQL, you need to have a comprehensive understanding of the advantages and drawbacks of both of them.
Pros/Advantages of SQL
No prior knowledge of extensive coding is needed. SQL is simple and easy to learn with declarative commands.
SQL is highly portable and can be run on Laptops, Mainframes, PC’s, tablets or smartphones, etc.
SQL is an open-source product that ensures a stronger community for development and assistance in this domain.
- Interactive Language
SQL is an interactive language which means it is easy to learn and quite efficient in working with complex queries. Programmers prefer this language as data retrieval in SQL is rapid.
- Defined standards
SQL standards are well defined as they were foremostly used by ISO and ANSI.
- Data Views
Allows multiple data views
- SQL supports the client-server architecture completely.
- High Demand
SQL is in high demand. Many top tier companies are using RDBMS and require administrators with proficiency in SQL skills. Companies like Micorosoft, Hootsuite, Cognizant, and many others are using SQL databases.
Cons/Drawbacks of SQL
- Complex Structure
Access is difficult in SQL because of its complex structure.
The process of interfacing can get complicated in SQL as there is not much coding involved in writing SQL queries.
SQL demand and scaling are limited to particular projects and data types like you cannot use SQL to query unstructured or semi-structured data. It is fixated on a relational schema.
Pros/Advantages of NoSQL
- Scale-Out Architecture
NoSQL was designed in 2000 to cover the concerns faced in SQL. It is inevitable to stop the exponential growth of data and to manage that NoSQL provides a scale-out architecture. This technology will allow changing the data plane resources by adding more nodes to the cluster that ensure larger storage capacity and scalability of data.
- Data Type Storage
NoSQL flexibility is its biggest advantage. Programmers are not limited to storing only structured data. The freedom from the predefined schema allows NoSQL databases to store and retrieve data easily. From structured data to loosely structured values like maps, strings, binary values etc, can all be stored and retrieved at ease by the data administrators.
- Developer Friendly
There is not much hassle in storing and using data for creating applications in NoSQL. Programmers can store data “as it is” i.e., without converting the semi-structured data into a table format for retrieval and manipulation. This enables developers to adapt to structure and technology on their own.
- Less Management
NoSQL databases are an enhanced version of a database management system and, thus, does not require a big team of data administrators to perform small tasks or to manage the system. In addition to this, the less complex structure of NoSQL makes it easier to handle and operate.
- Big Data Applications
NoSQL databases have a large capacity to store massive volumes of data.
Cons/Drawbacks of NoSQL
- ACID properties
Unlike relational databases, NoSQL does not support ACID properties that limit it to provide reliability functions.
- Query Language
NoSQL databases do not have any standard query language like SQL. It makes the process of data handling, retrieval, and management more complex and slower.
- Different Data Models
NoSQL has different data models for storing and maintaining data like Key-value, document, column family,etc. It hampers NoSQL to facilitate a single database for different purposes instead one has to operate with multiple databases and data models to perform all the niches. This makes the functioning complex, and increases the chances for less data consistency.
- Huge Databases
Data quality and Data Duplication are two of the prime issues with NoSQL as it can store up to a massive amount of data without the ACID properties.
SQL vs NoSQL: Which is better?
The biggest and the debatable question to answer.
There is no denying the fact that both SQL and NoSQL are some of the best of their kind. SQL is the most in-demand programming language for RDBMS and NoSQL is the preferred software for storing structured, unstructured and semi-structured data.
And the answer to which one is better is – It all depends on your requirements and the project you are working on.
If you are looking for consistency, reliability, and a system to query structured data you choose SQL databases.
However, if you are looking to work faster and independently for storing and retrieving data like graphs, binary numbers, etc choose NoSQL databases.
The former focuses on complex queries, with data consistency and ACID properties whereas, the latter is more object-based and suitable for a huge amount of different types of data storage.
Therefore, before choosing your preferred option read about the difference between SQL and NoSQL thoroughly.
1. Can NoSQL replace SQL?
No, NoSQL cannot replace SQL as certain projects require SQL only.
2. Where is NoSQL used?
NoSQL is used by companies that need a distributed data system for storing and maintaining a large amount of unstructured and structured types of data.
3. Where is SQL used?
SQL is used by administrators who want to retrieve, store and manipulate data for different purposes. SQL supports only relation-based databases only.
4. Is SQL safer than NoSQL?
Yes, SQL is safer than NoSQL for complex queries in terms of data consistency, data integrity and data redundancy as SQL adheres to ACID properties.