There are various types of databases used today in the industry. Some are SQL databases; some are NoSQL databases. To find the best database, we need to understand the difference between SQL and NoSQL databases. This article will explore the differences between SQL and NoSQL with a deep-dive.
What Is the SQL Database?
SQL is a database language most commonly used for updating databases, executing queries, and managing permissions. Designed for relational database management systems, SQL's major applications include writing integration scripts, setting and running analytical queries, and addition, update, and deletion of data rows and columns in a database.
What Is NoSQL Database?
NoSQL is a database system that, as it says in the name, does not use Structured Query Language (SQL) to submit queries. By using NoSQL databases, you can store large volumes of unstructured data. As expected, this results in much better throughput, read/write speeds - allowing for scale out of servers horizontally. A very popular NoSQL system is MongoDB, which uses JSON (Javascript Object Notation) to formulate queries.
What Are the Types of NoSQL Databases?
NoSQL databases are categorized into 4 major types. Let’s discuss each type for a better understanding:
- Document databases store data in a document, often in something like a JSON document. The values can be of different types, including strings, numbers, boolean, arrays, or objects.
- Key-value databases store data in unique key-value pairs, meaning each key is associated only with one value in a collection. We commonly use it for storing user preferences or caching.
- Wide-column stores data in the form of tables, rows, and dynamic columns. You can group related columns into column families. Individual rows then make up a column family.
- Graph databases store data in edges and nodes. A node represents an entity, like a user, category, or a piece of data. A relationship defines how two nodes are associated.
SQL vs NoSQL
|
Key Areas |
SQL |
NoSQL |
|
Type of database |
Relational database |
Non-Relational database |
|
Schema |
Pre-defined schema |
Dynamic schema |
|
Database Categories |
Table-based databases |
Document-based databases |
|
Language |
Structured Query Language |
Un-Structured Query Language |
|
Complex Queries |
Good for complex queries |
Not a good fit for complex queries |
|
Online Processing |
Used for OLTP |
Used for OLAP |
|
Base Properties |
Based on ACID properties |
Based on CAP theorem |
|
Scalability |
Vertically scalable |
Horizontally scalable |
|
Auto Elasticity |
Requires downtime in most cases |
Automatic, No outage required |
|
Examples |
MySQL, Oracle |
MongoDB, Cassandra |
Image credit: couchbase
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Conclusion
The above article would have provided you the differences between SQL and NoSQL databases. Every business will have their preference of databases based on their requirements. Choosing the right database is critical in achieving performance or uptime goals.
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