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Difference Between SQL and NoSQL
Both SQL and NoSQL Databases have their set of advantages and disadvantages. SQL databases can be considered when you are looking for data consistency, reliability, integrity, and when the data is structured. NoSQL databases are a much better option if the data is large, semi-structured, or unstructured and you are looking for faster storage and retrieval of data.
With so many databases available in the market, it can get a little challenging for an enterprise to decide whether they should choose an SQL Database or a NoSQL Database. This article will show you the key differences between the two types of databases and what is the best scenario to use each one of them.
What is SQL?
SQL stands for ‘Structured Query Language’. It is the most common programming language used for executing queries, and handling data by using CRUD (create, read, update and delete) operation on a Relational Database Management System (RDMS) like MySQL, PostgreSQL, etc.
When to Use SQL?
SQL databases are cross-platform, more secure, free, and open source with better and stronger community support. These types of databases are a much better option when −
Your primary focus is on data consistency, validity, and data integrity
You need to execute dynamic and complex queries to retrieve data
You have predefined data and defined SQL structure or schemas, which don’t change with the data
What is NoSQL?
NoSQL stands for ‘Not-Only SQL’. These types of databases are Non-Relational or non-tabular. A No-SQL database does not require a specific schema and hence is schema-less, and all the entries/documents are JSON documents. Examples − MongoDB, DynamoDB, Redis, etc.
When to Use NoSQL?
NoSQL databases are very flexible, easy to use, developer-friendly, and provide higher performance. These types of databases are a much better option when −
You have Big Data Applications that handle large volumes of unstructured data.
You need to scale the database based on constantly changing requirements
You need the flexibility to store different types of data
Differences between SQL and NoSQL
The following table highlights the major differences between SQL and NoSQL −
Key |
SQL |
NoSQL |
|---|---|---|
| Type |
SQL databases are classified as Relational databases, i.e., RDBMS. |
NoSQL databases are known as non-relational or distributed database. |
| Language |
SQL databases use standard Structured Query Languages, as the name suggests. SQL is an industry-standard and very powerful language to execute complex queries. |
NoSQL database has dynamic schema for unstructured data. The data stored in a NoSQL database is not structured. Data could be stored as document-oriented, column oriented, graph-based or organized as a Key-Value store. The syntax can vary from database to database. |
| Scalability |
SQL databases can extend their capacity on a single server by increasing their RAM, CPU or SSD. SQL databases are scalable vertically, as their storage could be increased for the same server by enhancing their storage components. |
In order to increase the capacity of a NoSQL database, you would have to install new servers parallel to the parent
server. NoSQL databases are horizontally scalable which means they can easily handle more traffic by adding new servers to the database, which makes them a great choice for large and constantly changing databases. |
| Schema |
SQL databases have a fixed, pre-defined schema, which makes the data storage more rigid, static, and restrictive. |
NoSQL databases don’t have a pre-defined schema, which makes them schema-less and more flexible. |
| Internal implementation |
SQL follows ACID (Atomicity, Consistency, Isolation and Durability) properties for its
operations. |
NoSQL is based on CAP (Consistency, Availability, and Partition Tolerance). |
| Data Storage |
SQL databases can only be run on a single system and because of this, they don’t follow the distribution of data and hence
they don’t support hierarchical storage of data. |
NoSQL Databases can run on multiple systems, and hence, they support data distribution features like data repetition,
partition, etc., making them the best option for hierarchical storage of data. |
| Type of Data |
SQL databases are table-based databases which makes them better for multi-row transaction applications. |
NoSQL is document-based, key-value pair, and graph databases, which makes them better when there are a lot of changes in the data. |
| Performance and suitability |
SQL databases are best suited for complex queries but are not preferred for hierarchical large data storage. |
NoSQL databases are not so good for complex queries because these are not as powerful as SQL queries but are best suited for hierarchical large data storage. |
| Examples |
SQL databases are implemented in both open source and commercial databases such as like Postgres & MySQL as open source and Oracle and Sqlite as commercial. |
NoSQL is purely open source. Some of its famous implementation are MongoDB, BigTable, Redis, RavenDB, Cassandra, Hbase, Neo4j, and CouchDB. |
Conclusion
The key difference between SQL Relational and NoSQL non-relational databases is the programming language used for executing queries. SQL databases store data in a more structured form and hence, they are preferred for more complex operations which could be completed with complex SQL queries. NoSQL does not have any declarative query language and the language varies from database to database, which is not so good for complex queries but an ideal choice for fast queries.
So, if you want to know "Which database is better for you?", then the answer majorly depends on your requirements and the data you are working with. You can start by deciding whether you want to go for relational databases or non-relational databases for your project. And then, you can further narrow down your options by considering the various SQL and NoSQL database options available in the market.
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