Amazon Aurora is a database service/engine that provides enhanced and organized data in table form. AWS Aurora is compatible with other cloud database services like MySQL and PostgreSQL, making it seamless to migrate, easy to manage, and exceptionally useful.
AWS Aurora is managed by Amazon Relational Database Service (RDS)-an engine that automates extensive administration works like database organization, storage, and backup. Aurora Users enjoy up to five times MySQL and three times PostgreSQL speeds with the existing systems. Furthermore, its high storage capacity can scale up to 64 Terabytes of database size for enterprise use.
Amazon Aurora Features
Enhanced Performance and Scalability
AWS Aurora performs five times better than the traditional MySQL and provides efficient results when coupled with the same hardware. Its operation services and techniques like quorums enable users to scale database preparation according to their specific needs. That means customers can have an additional fifteen low latency scan replicas across all three preferred zones. Storage-wise, Amazon Aurora provides up to 64 Terabytes of database size.
Data security is among the top features of Amazon Aurora. AWS has advanced security features that store data in an encrypted virtual network accessible to a limited number of users. The firewall operates through a primary management service that passes information through SSL, making it safe. Users can also go through data logs and view snapshots of various operations performed on the database.
Availability and Durability
The Amazon Relational Database Service (RDS) managing the AWS Aurora keeps track of your database health and ensures that the backup is updated. It safeguards data by isolating the database buffer cache and protects it during database restarts. Whenever there is a database failure, the RDS looks for Amazon Aurora replicas and uploads the backup data to the AWS Aurora database. Users can also make multiple Amazon Aurora replicas to prevent storage failure.
AWS Aurora makes it easy for customers to navigate various features provided through multiple monitoring interfaces by storing all customer operations in a logbook. An auto-update feature also ensures that your data is backed up through several patches- simplifying database management.
Amazon Aurora also has a cloning feature that allows users to clone terabytes of data in minutes, thus saving time.
Cost is one of the major factors that dictate the demand for software. AWS Aurora ensures that it remains affordable by charging its customers only for the data management service and storage used. It also uses various cost-effective measures that make it easier for users to optimize costs.
AWS Aurora architecture
The Amazon Aurora focuses on reusing its primary components like transactions, data recovery, and query execution, thus making it more efficient, affordable, and fast. The software design has undergone several updates recently to enhance its user experience and overall output. Some of the updates include:
- Creating and using various virtual data clones for safe data backup.
- Updating and storing change log on remote disk to prioritize data security and accessibility.
- Use of primary-replica setup whose sole function is to avail information.
MySQL and PostgreSQL Compatibility on Amazon Aurora
There are two versions of MySQL- MySQL 5.6 and MySQL 5.7. Both versions are compatible with the AWS Aurora, thus improving users' data management services. Although the Amazon Aurora does not function with MyISAM, it is still compatible with the InnoDB storage engine.
If you use MyISAM as your primary system for data storage, you will need to transfer it to InnoDB for you to access it through AWS Aurora.
It is easy to set up the AWS Aurora with PostgreSQL as it is compatible with PostgreSQL 9.6 and PostgreSQL 10 versions. Using PostgreSQL with the Amazon Aurora increases the efficiency and throughput of information relayed on the database. One can launch a PostgreSQL compatible Aurora function from the Amazon RDS console and use PostgreSQL and AWS Aurora as the primary engine.
Advantages of AWS Aurora
- Security: Since AWS Aurora is a product of Amazon, customers can be sure of data security and other features like IAM. It also uses 256-bit data transfer encryption that transfers customers' data via a secure medium.
- Scalability: Amazon Aurora has a dynamic scaling feature that can automatically scale up or down depending on user settings and database demands.
- Availability: Multiple database replicas in numerous zones guarantee high data accessibility and availability.
- Management: Amazon Management Console makes it easy to set up the Aurora cluster- a user can easily code an API or make a call through the RDS console.
- Cost-effective: Every business aims at making profits and optimizing expenses. Using AWS Aurora makes this goal a reality as you will only pay for the storage services used by your system.
AWS Aurora Pricing
Amazon Aurora pricing depends on one's usage and operations performed. The data storage is priced on rates per GB used, while the operations per million bases. Customers are not charged upfront fees, though you might incur extra charges added on features like snapshot exports, backtrack, and data transfer from AWS aurora to the Global database. The pricing is the same on both MySQL and PostgreSQL.
- On-Demand Instance Pricing: One pays only for the service users and is billed per DB.
- Database Storage and Input Outputs Pricing: Customers pay per GB used and as per the number of operations. Billing is usually done monthly, depending on the workload and database engine. The rates are as follows; Storage rate- $0.10/GB per month and I/Os- $0.20/million requests.
- Global Database: An optional feature offered by AWS Aurora focusing on proving low reads and data backup. The customer pays for replicated write operations between primary and secondary regions storage, regional data transfer, and other features vital in data recovery. The charges are $0.20 per million replicated write I/Os.
You can learn more about pricing on this page.
AWS Aurora best practices
When using Amazon Aurora, it is essential to follow best practices in order to get the most out of the database. This includes using the right instance type, configuring security groups, using the right storage type, and more.
Use the right instance type.
When choosing an instance type for Amazon Aurora, it is crucial to choose one optimized for Aurora. This instance type will have the best performance and offer the most features.
Configure security groups
It is vital to configure security groups to protect your Amazon Aurora database. By default, Aurora is not accessible from the Internet, so you need to create a security group that allows access from your specific IP address.
Use the right storage type.
When configuring storage for Amazon Aurora, it is essential to choose the right storage type. Aurora offers two storage types: magnetic and SSD. Magnetic storage is less expensive but has lower performance, while SSD storage is more costly but has higher performance.
It is crucial to backup your Amazon Aurora database often. Aurora offers two types of backups: automatic and manual. Automated backups are taken daily and are stored for seven days, while manual backups are taken on-demand and can be stored for up to 35 days.
Use the right tools
There are several tools available to help you manage your Amazon Aurora database. These tools can help you perform tasks such as creating and restoring backups, monitoring performance, etc.
AWS Aurora is a cloud-based relational database service designed to be compatible with MySQL and PostgreSQL. You can learn more about Aurora on the official website.