There are many different database options available to businesses today. Two of the most popular are Amazon Aurora and RDS. But which one is better for your business?
Aurora and RDS are both managed Amazon Web Services (AWS), so you must pay Amazon to manage and oversee your database. They also allow you to create databases on the console with a few mouse clicks. With terabytes of capacity for each database, Aurora and RDS can scale to astounding heights. Though they are similar in many ways, still, they have their differences.
Aurora is a relational database specifically designed for the cloud. It combines the simplicity and low cost of open-source databases with the performance and availability of typical enterprise databases. It is fully managed and compatible with MySQL and PostgreSQL.
RDS is a managed SQL (Structured Query Language) database service. Like Aurora, it is provided by Amazon. RDS supports many database engines for storing and managing data. It also covers maintenance activities like data migration, backup and recovery, and patching relating to relational databases.
We will discuss Aurora and RDS to understand their differences. We will list the features, pros, cons, and differences to help you make a better choice.
Aurora vs. RDS: A Side-by-Side Comparison
|What is it?||Fully managed relational database compatible with MySQL and Postgres SQL||Managed SQL database service|
|Developers||Amazon Web Services||Amazon Web Services|
|Released||October 2014||October 26, 2009|
|Service||Built for the cloud||Open-source cloud database service|
|Service||Infrastructure as a Service (IaaS)||Platform as a Service (PaaS)|
4 Must-Know Facts About Aurora vs. RDS
- In an Aurora database, data is separated into 10GB blocks and spread over many disks, with a storage capacity of 10GB to 64TB.
- RDS performs automatic database instance backups, daily data snapshots, transaction log preservation, and point-in-time recovery.
- Aurora provides simple scalability — storage is expanded automatically as the database expands, and you can set up to 15 Read Replicas to serve more read requests.
- RDS automatically updates database engine software. It allows database replication with automated failover across several availability zones to increase the dependability and availability of workloads.
Aurora: Complete History
Amazon’s Aurora was released in 2014. Back then, it offered compatible services for MySQL, an open-source relational database management system. In August 2017, the developers added another feature, Aurora Fast Cloning, which enables clients to make copies of their database.
Later, in October 2017, Amazon added compatibility with PostgreSQL, a free and open-source relational database management system. May 2018 saw the launch of Aurora Backrack, which enables developers to rewind database clusters without building new ones. As of September 2018, Aurora clusters stopped, and Amazon made the first serverless version within the same year.
For significantly revamping rational database storage for cloud contexts, Aurora developers won the SGMID System Award in 2019.
Features of Aurora
Let’s discuss some features of Aurora for more understanding.
Performance and Scalability
According to Amazon, it offers five times the performance of a regular MySQL. That is ideal for most business databases, depending on how their demands change. They can quickly scale up and down their database preparation from smaller to larger instances.
One of the best features of Aurora is scalability. It automatically increases the database volume size per storage need. The volume increases to 10GB and can reach a maximum of 128TB. This conveniently meets the required storage needs for many businesses.
By utilizing the AWS Key Management Service (KMS) and Amazon Aurora, you can efficiently encrypt your database and maintain high levels of data security. The underlying storage is encrypted when a database instance uses Amazon Aurora encryption for data storage at rest. Also, Aurora uses Secure Sockets Layer (SSL) to keep your data secure while in transit.
Easy to Use
It is easy to use Aurora. You can use the Amazon RDS Management Console, a single API call, or the CLI to access the new Amazon Aurora database instance. Amazon Aurora database instances are set up with settings and parameters relevant to the chosen database instance type. Additionally, you can start a database instance and link it to your application without first configuring it.
You are charged for the processing power and storage you have used. There are no other extra upfront charges. Once you pay your monthly payments, you are good to go.
You can move your local database to Aurora using the pg-dump and MySQL dump commands.
Availability and Durability
This storage is fault-tolerant and self-healing, designed for the cloud. It offers the availability of 99.99% with six copies of data replicated across three different availability zones. This improves safety and minimizes the chance of storage failure.
Pros of Aurora
- Failover time is faster
- 15 read replicas
- Regular backups
- Good speed
- Open-source compatibility (MySQL and PostgreSQL)
Cons of Aurora
- Supports MySQL-5.6.10; thus, you can’t use it if you want additional features or if you have an outdated version of MySQL
- Currently, you cannot use MyISAM tables. Aurora only supports InnoDB.
- You can only use r3large, so if you have a small RDS, it is impossible to use.
RDS is designed to make it easier to set up, run, and scale a relational database for use in applications. Because of its design, it is a simpler system for users. Let us look at some of its features.
Features of RDS
- It replaces the host automatically if the hardware fails or stops working.
- You don’t need any upfront payment. They charge the resources you have used. Further, they offer pricing models like “On Demand” or “Reserved Instances”.
- Security is taken care of, especially when accessing their database and services.
- RDS controls the time of automatic backups and stores up to five times worth of translation log backups.
- Users can take snapshots of their database instances saved in Amazon S3 once daily.
Pros of Amazon RDS
- Has an automated backup
- Hardware maintenance
- Automatic failover and simplified disaster recovery
- Automated storage allocation.
Cons of Amazon RDS
- No guarantee of CPU and storage performance
- Doesn’t offer a guarantee on data loss
- Doesn’t have automated compression management
- No automated performance tuning
- Doesn’t have root access to the server
- Only has five read replicas
Aurora vs. RDS: Which One Should You Use? Which Is Better?
So, which is the best choice? Aurora would be ideal, because it has excellent security, scalability, performance, availability, operational cost, and management capabilities. However, let us look at their differences to back our argument.
When you look at the performance, you will notice Aurora offers fives times the standard throughput performance on a regular MySQL, or two times on PostgreSQL. Additionally, it doesn’t store log buffers — it writes them to the storage.
RDS leverages SSD storage for I/Q throughput performance. It also has SSD-backed storage options from which you can choose, one for high-performance OLTO and the other one for cost-effective use.
So, if we compare Aurora and RDS speed, Aurora is consistent and reliable.
With RDS, there is a chance of data loss in case of a failover because they read replicas manually. With Aurora, they read the replica automatically and quickly if failover happens. That means data loss is impossible.
Furthermore, Aurora increases its database, which does not affect its performance. With RDS, you set your storage limits. The rest is done by auto scaling.
You will notice significant differences in the features, pros, and cons. The above are some essential differences that make us believe Aurora is your best choice.
Aurora’s unique features give you better scalability and performance than RDS. Though their prices are a bit higher, they are ideal for read-intensive workloads for businesses. Learn more about AWS services and do a comparison on various aspects to make an informed decision.