What is Amazon RDS and Is There a Better Alternative

Introduction

In our cloud native world, enterprises are handling more data than ever. A survey by IDG showed that the total size of data under management averaged almost 348 Terabytes. For app developers, databases are the de facto standard for data storage. The challenge is that building, maintaining and securing database services on top of an application is a task by itself - you need to install patches and updates, maintain backups according to your backup policies, and monitor the performance of the database management system that you choose to run. To make the management of those critical operational tasks easier, Amazon provides a relational database service called Amazon RDS. In this article, we will discuss the features and benefits of Amazon RDS and compare it with some alternatives in the managed database sector.

What is Amazon RDS

Amazon RDS is a managed SQL database service that makes it easy to set up, operate, and scale a relational database in the cloud. It provides resizable capacity while managing time-consuming administration tasks such as hardware provisioning, backups, software patching, monitoring and crash recovery. Amazon RDS automatically detects and recovers from instance and disk failures with minimal impact on applications. 

With Amazon RDS, you can run a relational database on AWS without worrying about setting up, managing, and scaling a relational database management system. You can use the RDS console to manage your Amazon RDS resources and perform basic database administration tasks for your DB instances. You can also use the AWS CLI, the AWS SDKs, or APIs to manage your Amazon RDS resources.

Amazon RDS gives a choice of multiple types of database engines:

1. RDS for MySQL
2. RDS for MariaDB
3. RDS for PostgreSQL
4. RDS for Oracle Database
5. RDS for SQL

• Manageability: One of the main benefits of Amazon RDS is helping enterprises to manage complex and large relational databases.
• Ease of use: With RDS, you don’t need to worry about learning various database management tools. You can run multiple database instances using one unified management console
• Time-effective: As maintenance tasks such as backing and patching are automated, time spent maintaining instances is reduced.
• Availability: Amazon RDS makes sure that your data is available at any time and any location via Multi Avalaibility Zone deployment which maintains a redundant copy of your data in a separate location.
• Scalability: Amazon RDS splits compute and storage making it easier to scale them independently.

But is there a better alternative?

Although Amazon RDS has many benefits, it comes with some limitations, too. When you start using RDS, it may look cost-effective and inexpensive but with growing database resource demands, the cost can increase exponentially. With RDS, you don’t have full control of all the runtime configuration of your databases - it can be difficult to extend the database engine with additional configuration or integrate non-Amazon plugins and extensions. The biggest limitation is in a disaster recovery scenario, where spinning up a new RDS cluster can take more than 10 minutes.

To overcome these challenges, enterprises are shifting to build their application using a Kubernetes-native database operator with container-native storage like Ondat. 

Let’s see how a Postgres operator like EDB and Ondat can work together:

• Ondat provides dynamic volume provisioning to make the management of persistent storage easy.

• EDB provides the automation and logic to enable easier management of the database and abstractions for common operational processes

• EDB with Ondat is entirely configurable from the Kubernetes level, enabling developers to rapidly create, scale and terminate databases according to business requirements with the same interface they use to manage their applications.

• EDB with Ondat enables you to use the same pool of resources for databases that you do for any other compute and storage workload and to control scaling yourself. The EDB operator can create and run databases tailored to your use case that are entirely within your own environment and under your full control. 

• Ondat features enable EDB to make the best use of any type of storage, on-premises or in-cloud enabling a consistent configuration to be used to provide high availability with disaster recovery at the data and application levels in any environment and on any platform. On AWS, storage can be chosen that best fits the use case whether high-performing EC2 Instance Store or IO2 or cost-efficient GP3.

• Ondat adds per-volume encryption, enabling a fine-knit federation of database access. Each database can be controlled individually with this configuration and is within a single application failure domain, greatly decreasing operational risks versus a common 'all-in-one' RDS topology.

• Ondat provides best-in-class replication and resilience, enabling workloads to continue running even in disasters that would impact RDS availability such as availability zone failures.

• EDB with Ondat can help you reduce your operational cost by up to 50% - instead of paying for an abstracted ‘vertical’, you pay for the raw storage and compute you require. This pool of storage and compute can be shared across your other workloads.

Conclusion:

RDS makes it easy to set up, operate, and scale a relational database in the cloud but if cost and budget is an important factor in your organization, using a database operator like EDB with Ondat is often the best option to reduce operational costs. With Ondat's recently launched community edition, you can run your application with no limits on clusters and nodes and with all the features like industry-leading performance, snapshots, and volume encryption.

Sign up for Ondat's new community edition providing unlimited nodes and upto 1 TiB per cluster for free. For more information on how to get started, visit our docs site.