NoSQL

Today I will go through about NoSQL including their database types.

NoSQL is a non-relational DMS, does not require a fixed schema, avoids joins and is easy to extend. The purpose of using a NoSQL database is for distributed data warehouses with large data storage needs. NoSQL is used for big data and real data. real-time web applications. For example, companies like Facebook, Google collect lots of user data every day.

The NoSQL database stands for “Not just SQL” or “No SQL”.

NoSQL databases are ideal for many modern applications, such as mobile, web, and gaming devices, which require flexible, scalable, high-performance, and highly functional databases to provide excellent user experiences.

Flexibility: NoSQL databases generally provide flexible schemas that allow for faster and more iterative development. The flexible data model makes NoSQL databases ideal for semi-structured and unstructured data.

Scalability: NoSQL databases are generally designed to scale by using distributed hardware clusters instead of scaling by adding expensive and robust servers. Some cloud providers handle these operations behind the scenes as a fully managed service.

High Performance: The NoSQL database is optimized for specific data models and access patterns that allow higher performance than trying to achieve similar functionality with relational databases.

Highly functional: NoSQL databases provide highly functional APIs and data types designed specifically for each of their respective data models.

You have heard of many different NoSQL databases, such as MongoDB, DynamoDB, Redis, etc. Now you may be wondering why we need so many different NoSQL databases. The reason is that different NoSQL databases focus on solving different problems.

Document-oriented databases

These databases allow storing complex nested documents, while most relational databases only support one-dimensional rows. It can be useful in many cases, for example if you want to store information about a user on your system and allow each user to have multiple addresses. With a document-oriented database, you can simply store a complex object with an array of addresses, while a relational database forces you to create two tables: one for user information and one for addresses.

Key value databases

Key value databases generally implement the simplest NoSQL model. Essentially, they provide you with a distributed hash table that allows you to write data for a specific key and read the data with this key.

Graph databases

Many domains, such as social media or information about movies and actors, can be represented as a graphic. While you can represent a graph using a relational database, it will be difficult and cumbersome. If you need to graph data, you can use specialized graphical databases that can store information about a graph in a distributed cluster and allow you to implement graphing algorithms efficiently.

Column store databases

The main difference between column store databases and other types of databases is how they store data on disk. Relational databases create one file per table and store values ​​for each row sequentially. Columnar databases create a file for each column in their tables.

I think you might get lots of things relating with NoSQL after reading this article. See you again.

Yuuma