Amazon Aurora..Go for it!

Updated 6 January 2022

Databases are necessary for the company’s apps to run. A company’s databases should expand in order to give better service. They should be bigger, faster, and more dependable as the company grows.

Amazon Aurora is a MySQL-compatible Relational Database that allows existing applications to continue to run without interruption. It performs five times better than MySQL on the same hardware.

If the user needs additional servers to read data from, he or she can add up to 15 Aurora replicas that store up to 128 terabytes of data. It also replicates data across three availability zones, and if a failure occurs, it fixes the issue promptly.

Amazon RDS manages AWS Aurora, which supports complex database activities, such as deployment, monitoring, and patching. The migration from basic MySQL to AWS Aurora is a smooth process that can be performed in a matter of minutes.

These services are available at a fair price with no upfront costs; you simply pay for what you use, and the user is charged for each hour they use it.

For more information about pricing, just click the link.


MySQL and PostgreSQL Compatibility

Amazon Aurora is a Relational Database that supports both MySQL and PostgreSQL. Therefore, you can use MySQL or PostgreSQL import/export tools to swiftly migrate from MySQL or PostgreSQL to Aurora. You can use the same code, apps, drivers, and tools that you do with other databases with Amazon Aurora.

High Performance and Scalability

Amazon Aurora outperforms MySQL by up to five times while costing a fraction of the price of commercial databases and retaining comparable performance and scalability. You can scale up or down your resources as your needs vary. Storage will expand up to 128 TB per database instance. For example, if we start with 10 GB and use more than 10 GB, the storage size is automatically rising up to 10 GB.

Highly Secured

Amazon Aurora protects the database on numerous levels. It provides network isolation via Amazon VPC and encryption via AWS Key Management Service that you create and control.

Fully Manageable

An Amazon Relational Database Service completely manages Amazon Aurora. You don’t have to bother about things like hardware provisioning, software patching, setup, configuration, or backups when it comes to database management. An Amazon Aurora backs up data to Amazon S3 on a regular basis and allows for point-in-time recovery. You can also keep an eye on your database’s performance with Amazon CloudWatch, a tool that quickly detects performance issues.

Availability and durability

It has a fault-tolerant and self-tolerant storage feature. It provides more than 99.99 percent availability by replicating 6 copies of data, two copies in each of three availability zones, and continuously backing up the data to S3. In less than 30 seconds, it recovers from a physical storage failure. Using the Global Database, a single Aurora database can extend across multiple AWS regions for faster read and disaster recovery.

Scaling of Amazon Aurora

  • The storage is automatically scales up to 10 GB if we start with 10 GB and consume more than that. In 10 GB increments, up to 128 TB can be added.
  • It keeps two copies of the data in each availability zone, with a minimum of three zones. As a result, we can say that it keeps six copies of the data.
  • It is design to transparently handle the loss of up to two copies of data without affecting database write availability and up to three copies without affecting database read availability.
  • Scalable compute resources include up to 32 VCPUs and 244 GB of memory.
  • It’s also self-healing, meaning that data blocks and drives are checked regularly for defects and automatically fix if any are found.


Aurora Replicas
  • Aurora Replicas are individual nodes in an Aurora DB cluster that are used to scale read operations and increase availability.
  • Up to 15 Aurora Replicas can be distributed across the Availability Zones.
  • The data in a DB cluster volume is represented as a single to Aurora Replicas in the DB cluster, and the data in a DB cluster volume is made up of numerous copies of data. The Aurora Replicas all provide the same query result.
  • Aurora replicas perform well for read scaling but not for write scaling in the DB cluster since they are completely dedicated to read operations. The majority of writing operations are handled by a primary instance.
  • Aurora Replicas are set as failover targets to increase availability, which implies that if one Aurora instance fails, the Aurora Replica is promote to the primary instance.
  • If your Aurora DB cluster doesn’t have Aurora Replicas, you’ll have to recreate the database instance to recover from the failure. Aurora Replica is faster than starting again with a new database instance.

Use Cases


It typically employs cross architectures that should be adaptable in terms of instance and storage scaling. Amazon Aurora enables businesses to focus on developing high-quality applications rather than worrying about the underlying database.

Enterprise Apps

Any firm that is already familiar with Relational Databases will benefit from Amazon Aurora. Aurora is cost-effective because its prices are 90 percent lower than those of others. Aurora optimizes tasks like provisioning, patching, backup, recovery, failure detection, and repair by being dependable and highly available.


AWS Aurora functions in the same way as a Relational Database, delivering high throughput, vast storage scalability, and high availability to the database.


As a result, in this blog, we explored how Amazon Aurora can assist the businesses in integrating while also increasing dependability and availability and cutting costs. In less than a second, Amazon Aurora reliably delivers over 500,000 reads and 100,000 writes.

To learn more about AWS RDS, simply click on the link.

In case of any help or query, please contact us or raise a ticket.

Category(s) AWS
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