Updated: Jun 10
The amount of data stored and sent has expanded tremendously as the world becomes increasingly connected and reliant on the internet. While the internet has transformed the way we work, live, and play, it has also presented a tremendous problem in keeping and managing digital information.
The amount of data consumed by companies is growing at an alarming rate, making database management systems that can keep up increasingly vital. To work with databases, we need a database language.
What is NoSQL? And the difference between SQL vs NoSQL
An SQL Server was created to store relational data as quickly as possible. Consumers, orders, and items can all be listed in a table and linked logically: customers put orders, and orders contain products. This close organization is beneficial for data management, but it comes at a cost: relational databases struggle to scale. They must maintain these connections, which is a time-consuming process that causes a lot of memory and processing power. It eventually cannot bear the load.
NoSQL databases differ from relational database management systems (RDBMS). NoSQL database is used if you need high scalability or when your data is too big or too complex for a traditional RDBMS. Additionally, NoSQL databases are often used when real-time access to data is required, and for handling big data.
Relational databases can scale vertically but not horizontally, whereas NoSQL databases can scale both vertically and horizontally. We can compare this to the construction of a building: vertical scaling entails adding more floors to an existing structure, whereas horizontal scaling entails the construction of additional structures. Vertical scaling is only achievable to a limited extent, but horizontal scaling is far more effective.
Popular NoSQL databases
Large corporations use NoSQL to store hundreds of petabytes of data and to process millions of requests per second. NoSQL databases are incredibly scalable and more adaptable than typical relational databases, making them excellent for schema updates. Consider this fact as an example of NoSQL scalability: Amazon's NoSQL database handled 45 million requests per second during Amazon Prime Day in 2019!
There are numerous types of NoSQL databases, each with its own set of advantages and disadvantages. MongoDB, Apache Cassandra, and Redis are some of the most popular NoSQL databases.
Why do NoSQL databases scale so well?
First off, they drop these costly relationships. NoSQL databases are extremely distributed is one reason they scale so effectively. This means that each database node can handle a significant amount of data and transactions. This enables the database to manage a high volume of traffic experiencing no performance degradation.
Also, NoSQL databases are more adaptable, as they are not bound by the strict table structure of a relational database. This means you can save data in any format you wish, which is useful for some applications. Each database entry in NoSQL has only two fields: a unique key and a value. For example, you can use the product's bar code as the key and the product name as the value for storing product information.
NoSQL databases use partitions to organize their data so that it is easy to query and update. Partitions also help maintain data consistency across multiple servers. Partitions are defined by keys, and NoSQL databases use a hash function to turn each item's key into a number. If a single database server is insufficient to store all of your data or perform all of your queries, NoSQL can share the workload between two or more servers. Each server will then only be in charge of a piece of your database. As an example, Apple maintains NoSQL database with 75,000 servers.
NoSQL is schemaless
Furthermore, NoSQL is schemaless, which means that each item in the database does not need to have the same structure. Every item can be unique. Therefore, you do not need a schema upfront to store data. As soon as you start adding data, the database will create a schema automatically.
This is in contrast to traditional SQL databases, where you have to create a schema before you can add data. NoSQL allows you to be much more flexible with your data structures, and you don't need to worry about changing your schema in the future.
Where do we use NoSQL?
When high scalability or flexibility is required, NoSQL databases are often used. A NoSQL database is used to store data from social networking apps, IoT devices, or user data for a web application. Cloud providers promote NoSQL because they can scale it more easily, such as AWS has DynamoDB, Google Cloud has BigTable, and Azure has CosmosDB.
NoSQL is a simple solution that solves two problems: where to store new things and how to find old ones. Calculating the hash of an item's key and keeping track of which server is in charge of which section of the keyspace is all that is required. On top of their own query capabilities, some NoSQL databases partially understand the SQL query language. There are many varieties of NoSQL databases, each with its own set of capabilities that can be useful in certain situations. Unstructured data, such as user-generated content and social media posts, can be stored in NoSQL databases.