As businesses expand, they rely on datasets to make informed decisions. This has led to an increase in demand for Data professionals. Almost all sectors, including Finance, Government, and Healthcare, rely on Data professionals. Deciding on a programming language for data storage can be challenging for professionals.
Structured Query Language (SQL) is a Data analysis tool used for storing data. Professionals must make a decision when it comes to using SQL versus NoSQL for Data Analytics.
In this blog, we will guide you through the differences between SQL and NoSQL, market trends in Data Analysis, salary insights, and various data analytics programs offered by upGrad that can help you become an expert in Data Analytics.
Also read: Thinking of a Career Switch: Is an Online Master’s in Data Science in Canada with it?
Choosing Between SQL and NoSQL in 2025 for Data Jobs in Canada
Canadian employers are seeking Data professionals with SQL and NoSQL skill sets. This section discusses the differences between these two, provides salary insights for the Data Analytics industry, explains when to use NoSQL vs. SQL, and outlines the prevailing market trends in Canada.
Understanding the Core Difference Between SQL and NoSQL
The core difference between SQL and NoSQL databases lies in the way they are stored, which determines their purpose.
- A SQL database follows a predefined structure.
- NoSQL database follows a flexible structure.
- SQL databases are suitable for complex requirements.
- NoSQL databases are well-suited for handling large amounts of data.
Market Trends for Data Roles in Canada
According to the Market Research Future report, the Canadian Data Analytics market is projected to reach 891 million CAD by 2025. The growth rate is expected to be approximately 30.83% from 2025 to 2035. Canadian organizations are focusing on the following developments in the Data Analytics market:
- Integrating AI technologies.
- Implementing Cloud technologies.
- Improving data security.
When SQL is a Better Fit for Data Professionals
SQL is better suited for storing and manipulating structured data. It helps the professionals belonging to these industries:
- IT: Cloud computing, Business Analytics, and AI Data preparation.
- Healthcare: Uses it for managing Electronic Health Records (EHR), performance tracking, and medical research.
- Banking and Finance: For fraud detection, maintaining security, and following regulations.
When NoSQL Makes More Sense for Canadian Employers
NoSQL is the preferred choice for semi-structured or unstructured datasets. Reputed organizations like Amazon, Facebook, and Netflix use it. The following industries mainly use it:
- Content management Systems (CMS) that support a variety of metadata or content.
- E-commerce platforms require a high volume of transactions and traffic.
- Social platforms to manage interconnected datasets and track consumer journeys.
Salary Insights and Growth Potential
The average annual salary of a Data Analyst in Canada is around CAD 72,213. There are different career options and growth potential for professionals. They can work in industries such as:
- Cloud.
- Analytics.
- Technology.

SQL vs NoSQL: Key Differences You Need to Know
Here’s a comparison table with the key differences between SQL and NoSQL.
Feature | SQL | NoSQL |
Data structure | A table containing rows and columns | Document, graph, or key value-based |
Query language | Structured Query Language | Varies depending on the query method (JSON, BSON) |
Scalability | Vertical (needs hardware upgradation) | Horizontal (needs more servers) |
Schema type | Fixed (predefined) | Flexible (dynamic) |
Use case | Finance, HR, Healthcare | CRM, Social media, Big Data |
Examples | MySQL, MS SQL Server | MongoDB, CouchDB |
Explore Career-Boosting Data Programs from upGrad Canada
upGrad offers a wide range of Data Science and Analytics programs in collaboration with reputable institutions. Our online courses provide flexibility and are more affordable than on-campus programs. Let’s have a look at some of our courses.
- Master of Science in Data Science from Liverpool John Moores University: This course can be completed in 18 months. It is targeted at professionals with a tech background, such as Data Analysts, Software Engineers, Data Scientists, or ML Engineers. Highlights of this course are:
- Free Python programming bootcamp.
- Group mentorship sessions.
- Experience learning with more than 100 programming tools.
- Executive Diploma in Data Science and AI from IIIT-B: This course can be completed in 12 months. It is also suitable for beginners, as a free programming workshop is provided. Highlights of this course are:
- Domain-based projects.
- More than 50 hours of programming fundamentals.
- More than 60 case studies.
🎓 Explore Our Top-Rated Courses in Canada
Take the next step in your career with industry-relevant online courses designed for working professionals in Canada.
- DBA Courses in Canada
- Data Science Courses in Canada
- MBA Courses in Canada
- Master of Education Courses in Canada
- AI ML Courses in Canada
- Digital Marketing Courses in Canada
- Product Management Courses in Canada
- Generative AI Courses in Canada
FAQs: SQL vs. NoSQL for Data Roles in Canada
Q: What is the main difference between SQL and NoSQL databases?
Ans: SQL databases use a predefined schema to handle multiple rows of transactions. NOSQL databases use a flexible schema suitable for documents or graphs.
Q: Is SQL or NoSQL better for data jobs in Canada?
Ans: There is no fixed answer to this question. It depends on the requirements and type of data used.
Q: Which is easier to learn: SQL or NoSQL?
Ans: SQL is an easy-to-learn programming language; NoSQL requires some time commitment and skills to learn.
Q: Are NoSQL skills in demand in 2025?
Ans: Yes, NoSQL skills are in high demand in 2025. They are required for Cloud computing, Big Data growth, and several website applications.
Q: Do data analysts in Canada use NoSQL?
Ans: Yes, Data Analysts in Canada can use NoSQL when flexible data storage is required. It is increasingly used in social media and e-commerce.