Data volumes are growing.
It is estimated that in just another two years, manual data management tasks will be reduced by as much as 45% with machine learning and automated service-level management.
A database comes in handy with storing, organizing, and managing large data volumes, also referred to as big data.
However, every database does not necessarily fit every business need.
Therefore, deciding on which type will best suit your business needs can be tricky.
SQL databases help you solve complex queries and analyze data.
Some of the most popular SQL databases are:
- Microsoft SQL Server
- Microsoft Azure SQL
NoSQL databases, on the other hand, work well with large data-sets and help reduce data latency.
Some of the most popular NoSQL databases are:
- MongoDB (Document-Based)
- Apache CouchDB (Document-Based)
- BigTable (Key-Value Store)
- Oracle NoSQL (Key-Value Store)
- Redis (Key-Value Store)
In this blog post, we take a look at the key differences between SQL and NoSQL databases to help you make an informed decision.
Let’s get started!
How Does an SQL Database Differ From a NoSQL Database?
Data structure is the most important factor that differentiates SQL from NoSQL databases.
So, do you need ACID compliance or BASE consistency?
- ACID refers to atomicity, consistency, isolation, and durability.
- BASE refers to basic availability, soft state, and eventual consistency.
ACID compliance helps you ensure that database transactions are completed in a timely manner.
Therefore, if you have structured data and need ACID compliance, then an SQL database is what you’re looking for.
However, if your goal is data flexibility and speed, then consider a NoSQL database.
Since an SQL database has structured data, it’s easier to write queries.
On the other hand, while a NoSQL database offers data storage flexibility, querying data isn’t as easy as compared to an SQL database.
In addition to this, you will need a developer or a data scientist to help you query data in a NoSQL database.
Therefore, the costs involved are higher with a NoSQL database.
SQL databases are vertically scalable.
You can do this by increasing CPU speed or RAM and SDD size.
This means that in order to scale your database, you will need to increase the capacity of one server.
In contrast, you can scale your NoSQL database horizontally by increasing the number of servers.
NoSQL databases are capable of becoming increasingly large and powerful to accommodate data that is constantly evolving.
Therefore, NoSQL databases help you deal with large data volumes as well as those that are constantly changing.
Which Database Is Right For My Business?
The most effective way for you to decide which type of database to go for is to analyze the functions you need the database to have.
An SQL database is what you should go for if a predefined structure and set schemas will help you, especially if you require multi-row transactions.
It will also help you with data consistency, without leaving room for error, such as with accounting systems.
On the other hand, you would want to go for a NoSQL database if your business is experiencing rapid growth with no set schema definitions.
Therefore, a NoSQL database gives you much more flexibility as compared to a relational database.
Furthermore, it helps you effectively analyze large quantities of data, as well as data that has a variable structure.
Get Enhanced Business Intelligence With Enterprise Data Warehousing!
In this blog post, we looked at the key differences between SQL and NoSQL databases.
A data warehouse helps you with improved data quality, timely access to data, as well as boosted data-query and system performance.
Popular Blog Posts
Data Lake vs Data Warehouse: Which one should you go for?
How to Leverage Data Layer with Google Analytics
Driving Effective Revenue Cycle Management Analytics for Healthcare
Top 5 Reasons Why Tableau is Leading the Business Intelligence Industry
An Introduction to the Key Components of Adobe Analytics and Benefits of Using It for your Enterprise
Data Warehousing and its Challenges