Amazon Aurora is a relational database engine for Amazon Web Services. It is MySQL compatible, which means that code, applications, and drivers used in databases that rely on MySQL can be used in Aurora with minimal or no changes. MySQL is an open source database management system based on the Structured Query Language ( SQL ).
Amazon RDS and Amazon Aurora
Amazon Relational Database Service (RDS) manages Aurora databases by handling provisioning, patching, backup, recovery, and other tasks. A developer can migrate to and from MySQL databases using the mysqldump (export) and mysql import (import) utilities or using the DB Snapshot migration feature of RDS. Data migration typically takes an hour.
Storage
Aurora stores a minimum of 10GB and automatically scales up to a maximum of 64TB. The service divides a database volume into 10 GB blocks spread across different disks. Each chunk is replicated in six ways across three AWS Availability Zones (AZs).
Recovery
If data in one AZ fails, Aurora will attempt to recover data from another AZ. Aurora is also self-healing, which means it performs automatic error checks of data blocks and disks.
Developers can increase the resources allocated to a DB instance and improve availability through Amazon Aurora Replicas, which share the same storage as the Elastic Compute Cloud (EC2) instance.
An Amazon Aurora Replica can be promoted to a primary instance without data loss, which helps with fault tolerance if the primary instance fails. If a developer made a replica of Aurora, the service automatically fails within one minute; it takes about 15 minutes to fail over without a replica.
Cryptography
For security, Amazon Aurora encrypts data in transit through the AWS Key Management Service. Automatic backups, snapshots, data at rest on the underlying storage and replicas on the same cluster are also encrypted. Additionally, Aurora DB Instances are created in an Amazon VPC, allowing users to isolate a database on their network for added security.
Pay per use service
Amazon is a pay-per-use service where a user pays per instance; Customers can opt for on-demand or reserve pricing. AWS also charges customers for any storage that Aurora uses in GB increments per month and per I/O rate (per million requests).
Aurora Serverless
Aurora Serverless is an auto-scale, on-demand version of Amazon Aurora, the high-performance relational database built for the cloud.
Administrators do not need to manage DB instances with Aurora Serverless as the database will scale up or down based on requirements and automatically start and shut down when needed.
This minimal overhead database model appeals to both startups and large companies. An IT team can deploy Aurora Serverless for a variety of use cases, primarily because it scales up and down with application requirements.
Finally, it is interesting to know that the database is suitable for an application with a variable or unpredictable workload, websites that occasionally see a spike in traffic, or unevenly distributed databases with random hops in queries.
Summary of Amazon Aurora Benefits
The top three benefits of using Aurora are related to simplicity, cost, and security. As mentioned, Aurora runs on Amazon RDS, so it's the same web interface you may already be using.
The heavy lifting and complexity when it comes to an enterprise-grade database in the cloud is often related to provisioning, maintenance, scaling, patching, backups and updates required, but RDS handles it all. For your team, the initial setup is similar to an open source database in RDS.
self-healing instances
In addition, DB instances are self-healing, scalable, and fault-tolerant, thanks to the connection between Aurora and Amazon S3 (Simple Storage Service), the object storage platform that works in conjunction with enterprise relational database instances.
Low cost
Cost plays an important role here, because typically expanding your Big Data project would require a huge investment in infrastructure. With Amazon Aurora, you can add up to 15 Read Replicas per instance simply by choosing this option. There is no management, planning or infrastructure development involved to achieve this high performance.
As you grow, Amazon S3 also grows to meet your storage needs, up to 64 TB per instance.
Downsizing is just as important—companies don't lose the investment they've made to tackle the biggest projects while it sits idle waiting for the next massive deployment.
Security
Endpoint security is a critical component of any big data project, especially in the age of data breaches and exposed user information that is often sold on the dark web. If a company like Ford is experimenting with Big Data projects with materials or components inside a new, unannounced vehicle, and the data hacked and exposed, this could be a major setback.
Aurora uses technologies such as network isolation, encryption at rest using key encryption, and encryption during data transmission using SSL. It's also important to note that because Amazon Aurora uses S3 for storage, this service is also highly secure — the underlying data used in the Big Data project is automatically archived on the same cluster. There is little opportunity for data leaks when the database itself and storage are so closely linked.
Can we show you what it is and what are the benefits of Amazon Aurora? make contact with us to chat with one of our experts and see how this relational database engine can help your business!
