What is the Difference Between SQL and NoSQL?

In the world of data management, there are two broad schools of thought. The first is that all your data should be stored in a structured database and indexed for ease of searching. The second is that you should use whichever tool best fits the problem you’re trying to solve — not necessarily the same tool for every problem. A NoSQL database is a type of non-structured database that can handle large volumes of dynamic data and need not be equipped with attributes beforehand. Traditional SQL databases, on the other hand, require data to be pre-organized and indexed before being searched. This article explains the primary differences between SQL vs NoSQL databases and why they matter so much in data management.


What is a SQL Database?


SQL, which stands for “Structured Query Language,” is a type of database designed for storing and querying structured data. SQL databases are the most common type of database used in commercial and enterprise applications. They are relational, which means they store data in tables linked to each other by columns. SQL is a standard language used to create, read, modify, and delete data in relational databases. For example, if you were managing a customer database, you’d likely have a table with fields like “name,” “phone number,” “address,” “email,” etc. If you wanted to get a list of all customers living in California, for example, you could use SQL to pull that data.


What is a NoSQL Database?


NoSQL is a family of non-relational data stores that don’t use SQL. NoSQL data stores were developed to address the issues found in relational databases, such as cost, scalability, and the ability to handle non-structured data. Such databases are often used together with traditional SQL databases to handle less structured data. As much as relational databases are great at handling structured data, such as customers, and inventory, they aren’t that good at handling unstructured data, such as images, videos, etc. This is where NoSQL databases excel. Whereas relational databases require data to be structured beforehand, NoSQL databases don’t require this structure.


SQL vs NoSQL: Why does it matter?


The two terms, SQL and NoSQL, may sound like jargon, but they actually have a significant impact on how businesses operate. Depending on the type of data you’re storing, the method you choose to collect, store, and retrieve it can have drastic effects on your costs and overall functionality. If you’re using an SQL database, you’ll have to have a clear idea of what data you’re collecting, how it’s structured, and why. You’ll also need to have a clear idea of how much data you’ll be collecting before deciding on an SQL database. In contrast, NoSQL databases are much more flexible. You don’t have to know the exact structure of your data ahead of time. You don’t even have to know how much data you’ll be collecting.


Key Differences Between SQL and NoSQL



Structured vs unstructured data: SQL databases are good for structured data, while NoSQL is good for unstructured data. While relational databases are great at handling structured data (customers, inventory, etc.), they aren’t effective at handling unstructured data (images, videos, etc.).
Indexing: SQL databases require data to be pre-indexed for efficient searching. This means that you have to know exactly what data you’re collecting, how it is structured, and what fields you want to search. NoSQL databases do not require data to be pre-indexed and therefore are more flexible.
Commercial vs free: SQL databases are commercial tools, while NoSQL databases are free tools. SQL databases have been around for a long time, so many businesses use them. Because these businesses are using the same tool to store their data, there are a lot of people who know how to use SQL databases.
Scalability: SQL databases scale vertically, while NoSQL databases scale horizontally. SQL databases make for a great single-server solution, but when demand increases and your data grows, all you need to do is increase the processing power of the existing servers. NoSQL databases make for a great horizontal solution. When demand increases, you just have to add more servers.

Conclusion


In summary, SQL and NoSQL are two broad schools of thought when it comes to data management. SQL databases are designed for structured data and require everything to be indexed beforehand. NoSQL databases are unstructured and store data more like a spreadsheet than a table. Depending on the type of data you’re collecting, the method you choose to collect, store, and retrieve it can have drastic effects on your costs and overall functionality. Mostly, SQL databases are commercial, while NoSQL databases are free. These differences should be taken into account when choosing the right tool for your data needs.

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