Do you know when to use NoSQL database instead of a relational database?
NoSQL databases continue to grow in popularity as organizations work to collect all types of data in one place.
But some developers still aren’t clear when to use a NoSQL database over a relational database.
Learn more about what SQL is and get a clear picture of ideal applications of relational databases and NoSQL databases.
Quick Overlook
What is SQL? (Also Known as Relational Databases)
Structured query language (SQL) allows you to create queries that create, read, update and delete from your database.
SQL is a universal language in that it applies to MySQL, PostgreSQL, and Microsoft SQL Server databases.
But SQL databases have limits in four crucial areas.
- Structure: data in SQL databases are stored within tables, that is rows and columns of information. You use unique identifiers to select rows and query that data.
- Storage: all data is stored within one node. It takes advanced coding to segment or partition the data in any way.
- Scale: scaling SQL databases is challenging because you’ll need to either add more machines or improve your machines to grow your database.
- Access: you’ll need to write create, read, update and delete syntax queries.
What Is NoSQL?
NoSQL databases offer large, distributed data storage. These databases can store structured, semi-structured, or unstructured data. You can store that data within a:
- Table
- Graph
- Document
- Key-value
The fastest NoSQL databases offer incredible scale and flexibility in how you can query the data.
That’s because these databases rely on hashing.
You can scale horizontally, which means storing the data in multiple databases (also known as sharding).
When to Use NoSQL Instead of a Relational Database
With a better understanding of how SQL and NoSQL databases function, here’s a look at the most common scenarios for when to use a NoSQL database instead of a relational database.
Flexible Data Storage
Traditional relational databases require a static data structure before you can even begin development.
Changing your database schema can be a costly endeavor and require hours of manpower.
NoSQL allows you to manage to change data models.
Constantly changing or evolving data is ideal for NoSQL or in cases where the data will be static but you don’t fully know the format until you get deeper into the development project.
Rapidly Scaling Data Storage Needs
Some applications start with very mild data storage needs.
But within a week of launching the app, you might have millions of users and data to store.
NoSQL is prepared to handle such a huge jump in capacity thanks to its seamless scalability.
Relational databases generally scale vertically, which means migrating data to a larger storage capacity server.
But thanks to modern data needs, you might complete one migration and need to upgrade again because growth continues to happen.
Because NoSQL isn’t hosted on a monolithic server, it scales to meet your ever-changing data needs with incredible speed and responsiveness.
Additionally, NoSQL databases are ideal for cloud storage because they are less expensive and faster.
High Volume of Users at Once
Concurrent performance is another key consideration for selecting your database.
If you will have many users accessing your database at once, consider a NoSQL DBaaS provider.
NoSQL can give you the option to avoid transactional lockdowns that prohibit editing data while another user is modifying it.
These practices can slow down relational databases immensely and cause latency issues.
While you might be trading off some consistency for performance, NoSQL can be great for simultaneous use without losing performance.
Fast Development Timelines
NoSQL databases allow developers to be far more agile since they don’t have to set the structure in advance of beginning application development.
If your development timelines are short and you need fast options for getting your application up and running, NoSQL is a great option.
Understanding Application Needs
When selecting your database type, you need to look at your application needs first.
This will inform whether a NoSQL or relational database makes the most sense.
Storing predictable, structured data that you want to make accessible to a set number of users might be a perfect use case for using a relational database.
But many other use cases are better suited to the more modern flexibility and options of a NoSQL database.
Learn more about how AI is changing NoSQL databases and download BangDB, a NoSQL database that employs machine learning to make unstructured data searchable and usable.