Ever wonder how Google stores its data? Google is the fastest search engine. It can store and categorize data from millions of websites. Google can find what you are looking for from your search query, filter through all the data and provide information in less than a second. How does Google do this?
NoSQL is one of the tools Google uses. NoSQL allows you to quickly store large amounts of unrelated data. Let’s take a closer look at NoSQL and how it can be used.
How NoSQL databases work [VIDEO]
Ben Finkel, SPOTO trainer, discusses the differences between NoSQL and relational databases, when to use each type of database and why NoSQL values speed, flexibility, over consistency, in this video.
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Get started trainingWhat is a NoSQL Database and how can you use it?
NoSQL can be either used to signify non-SQL, or it could refer to SQL depending on who you ask. NoSQL by its very nature is not relational. What does this mean?
We need to know about some other aspects of NoSQL in order to fully understand it.
First, computers need some kind of storage mechanism. There are many options for how to store data in applications. However, non-standard storage mechanisms can cause a lot more problems quickly.
Developers could create their own storage systems, and some do. Games, for example, use non-standard configuration files to store their video game settings. What happens if you need to store large amounts of data or share data with another program?
It is not surprising that there have been a few common ways to store data over the past few decades. Databases are a great tool for large data storage. This is what application developers, businesses, and others have decided. Databases are also great for quickly retrieving data.
This is the first thing that we need to know. Computer systems require a common way to store large amounts and retrieve it quickly.
A relational database was the standard for data storage in the 1970s. Relational databases store similar data together. Data is stored in different tables, with each table storing data as a spreadsheet. Data is relational. One table may contain customer information like names, addresses, phone numbers, and phone numbers, while another table might store login information.
Although relational databases can be extremely efficient and quick, they can be difficult to design and maintain. Before any database or application is created, you need to fully understand the data stored in it.
Although relational databases can be updated later on, these updates require a lot more work. Before the changes can be made to production environments, both the database and the application that uses it must be adjusted and tested. It takes a lot of planning to deploy those changes.
This is the second thing that we must understand. Although relational databases can be extremely fast and efficient, it takes a lot of work to create and maintain them.
NoSQL databases solved the problems with relational databases. NoSQL databases are not like relational databases. You don’t need to plan for the data that will be stored in them. They can store data.
This makes NoSQL databases ideal for certain applications such as IoT devices and search engines.
NoSQL databases can be used immediately because they require very little planning. This allows developers to develop, prototype, then deploy applications much quicker. Because NoSQL databases are able to adapt to changes and can be built quickly, they also fit the popular form of agi.