What is NoSQL?

There’s a joke popular in data engineering and science circles that goes like this: Two database administrators walk into a NoSQL bar and leave because they can’t find a table. The joke’s punchline alludes to the fact that, unlike SQL databases (relational databases), NoSQL databases are non-tabular—meaning they don’t have any tables!

As a budding data engineer or scientist, you may have played around with NoSQL databases like MongoDB and Cassandra. But how do these databases work, and how will you use them in your future career? Get a comprehensive answer to the question, “What is NoSQL?” below!

What Does NoSQL Mean?

NoSQL databases enable you to query and store data differently than a traditional relational database, which has a tabular structure and uses structured query language (SQL). A NoSQL database keeps data within a single data structure, such as a JSON document, rather than using a tabular structure, meaning it doesn’t need a schema like a relational database. That allows you to manage large amounts of unstructured and semi-structured data in the database.

To make things a little more complicated, NoSQL databases also function as distributed databases, meaning they handle data in a distributed computing environment. That’s a computing model where software components are shared among several computers or “nodes.” Because data is kept on multiple computer servers, either local or remote, a NoSQL database will continue to function even if one of those servers malfunctions. The result? You can always access the data you need in a NoSQL database because of its high availability.

NoSQL databases started in the late 2000s to counteract rising storage costs. At their core, these databases handle large amounts of unstructured and semi-structured data without additional engineering, making them more beneficial for storing large data volumes than relational databases in some use cases.

Enrolling in a data engineering or data science program from the Data Incubator will help you further understand the question, “What is NoSQL?” For example, the Data Science and Engineering Bootcamp lets you explore different databases and work with world-class instructors.

NoSQL Database Types

There are four main types of NoSQL databases:

Document databases store data in documents, with each document having different pairs of fields and values. These values might be numbers, objects, or strings.
Wide-column databases store data in rows and dynamic columns.
Key-value databases store data as key-value pairs, with each pair having a unique identifier.
Graph databases store data in edges and nodes.

The database you use for a data science or engineering project depends on your data type, whether you need to scale your database, and your specific use case. Most engineers and scientists use a combination of NoSQL database types, though it really depends on the assignment.

Pros of NoSQL Databases

Here are some advantages of NoSQL databases:

NoSQL databases are extremely scalable, and you can adapt them according to your data engineering or science workflows.
NoSQL databases require less maintenance than relational databases because they partition data across different nodes.
NoSQL databases handle large amounts of data, which makes them a good choice for large data projects.
NoSQL databases like MongoDB, Cassandra, and Amazon DynamoDB don’t require as much code as other databases, which makes your life as an engineer or scientist easier.

The Data Incubator’s Data Science Bootcamp is an immersive program based on real-world examples, helping you learn life-long skills. You’ll develop database experience from world-class data science professionals and create a portfolio to show employers.

Cons of NoSQL

Here are a few disadvantages of NoSQL:

SQL databases are older than NoSQL databases, meaning you’ll find more resources and support online for the former.
NoSQL doesn’t support atomicity, consistency, isolation, and durability (ACID) transactions for multiple documents, which ensures data validity for databases.

What are you waiting for?

Want to take a deep dive into the data science skills you need to become a successful data scientist? The Data Incubator has got you covered with our immersive data science bootcamp.

Here are some of the programs we offer to help you turn your dreams into reality:

Data Science Bootcamp: This program provides you with an immersive, hands-on experience. It helps you learn in-demand skills so you can start your career in data science.
Data Engineering Bootcamp: This program helps you master the skills necessary to effortlessly maintain data, design better data models, and create data infrastructures.

We’re always here to guide you through your journey in data science. If you have any questions about the application process, consider contacting our admissions team.