It’s a well-known, high-performance and highly scalable cloud RDBMS that works with MySQL and PostgreSQL relational databases. The Amazon Aurora RDBMS storage framework also can be configured based on database workloads. Amazon Aurora is five times faster compared to MySQL and three times than PostgreSQL. Aurora’s revolutionary storage infrastructure, which is specifically designed to take advantage of new cloud technology, is one of its most crucial features. Amazon AuroraĪmazon Aurora has two big advantages: It’s easy to use and offers device efficiency. Let’s consider the most popular Amazon relational databases. The relational data approach is not suitable for all domains.This is an important limitation that forces us to keep tables relatively small and optimize the database to scale. Since each query is against the entire table, the execution time of the query depends on the size of the table.OOP objects are not supported, so even representing simple lists can be a problem.However, why is this a disadvantage? Because there is a limit to the computing power of a computer and adding resources encourages downtime. Scaling is done by adding computing power to the computer on which the database is installed.You can limit or allow data access for specific users. Relational databases offer high security.Relational databases support atomic transactions.The entire database is stored on one computer, and the relationships between the records are used as pointers, that is, you can update one record and all records associated with it will be immediately updated. You have the ability to quickly update data.The simple structure allows you to effectively work with most data types.They use SQL (Structured Query Language), which is quite widespread and supports join operations by default.Data warehousing (is a term that refers to the process of storing).Apps for enterprise resource planning (ERP).CRM (customer relationship management) applications.On Amazon, there are a variety of uses for relational databases, which can be: With a relational database, you have access to more developers, need less support and have lower development costs. Here is a useful thing to remember: For ordinary projects, in technical terms, there is no difference which database to use, but economically it would be more beneficial to give preference to the most common MySQL, which is used by many content management systems or slightly less common in simple PostgreSQL projects. Generally speaking, relational databases are databases that are used to store and provide access to related parts of information. Table columns hold data attributes, and each record usually contains a value for each attribute, which helps to easily establish relationships between data items. Each row in a table is a record with a key (a unique identifier). The table must contain columns (with a data type) and rows (with records). All information in the database is always associated with other information and is presented in a strictly and logically structured way, including the fields that describe the data, the operations performed on them, their relationships with each other and the most important part - the rules that ensure their integrity. The distinctive feature of an SQL database is storing data in interconnected tables. Relational or SQL is the most common database AWS option. Let’s take a closer look at each of them. Both of these AWS database options are equally useful in their own way and are entirely possible to work with, but you can still find a ton of differences between them.īasiсally, we can classify AWS databases in the following way: There are two main AWS database types that we traditionally distinguish in the IT environment: relational (SQL) and NoSQL database management systems. Classification of the AWS Database Services In this article, we explain the difference between the two AWS database types: SQL and NoSQL, as well as discuss the capabilities, functions and features of the most popular services to help you choose the database that is a perfect match for your project. So before jumping right into making your decision, you should understand what AWS databases offer. Users constantly get confused at the point when they need to choose the database that works best for them and their project. The capabilities for capturing, saving, sorting and analyzing big data significantly differ. AWS provides a variety of data analytics resources that enable you to easily plan, scale, protect and deploy big data tools. Most likely you are already aware of what a database is and of its main functions - processing and storing data.
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