Amazon RDS – The Beginner’s Guide

by Nov 6, 2009

On the eve of Microsoft's announcement of the public release of SQL Azure Database, Amazon decided to release its own relational database service (RDS). This is something they seem to have resisted offering for a very long time. Maybe it was in the works, or maybe this was a preemptive action against their competition. Whatever it may be, such a healthy competition can do much good for the Cloud marketplace.

RDS brings with it the promise of MySQL on the Cloud. Having preferred MySQL for quite some time, we were anxious to get an AWS account and see what the hype is all about. Imagine our confusion when we signed up for Amazon RDS and all the AWS Management Console showed was the EC2 dashboard. There was no obvious way to get started using RDS.

Command Line Interface Tools (CLI)

At the time of this article, there is not yet a graphical user interface for RDS. The only way to use RDS is through the command-line tools. Setting up the tools, however, can be quite difficult: There are no installers per se; you have to download the zipped package to your instance, extract it, and set the environment, manually. Here's how we did it on a Windows XP box:

Prerequisites: The command-line tools are written in Java. So you need either JDK or JRE installed on your system.

Environment: There are a couple of environment variables that need to be set, manually:

  • The JAVA_HOME variable, which contain the path of the Java runtime installed on the system.
  • The AWS_RDS_HOME variable, which contains the path to the directory containing the CLI tools.

Based on the above, below is what we entered from the command-line:

C:\>set JAVA_HOME=E:\Java\jre6
C:\>set AWS_RDS_HOME=C:\Amazon RDS\CLI

Credential File: The zipped package containing the CLI tools also had a file named credential-file-path.template. We copied our AWS Access and Secret Keys to the place holders in the file, and then set another environment variable:

C:\>set AWS_CREDENTIAL_FILE=C:\Amazon RDS\CLI\credential-file-path.template

Path: Finally, we had to add the path of the CLI tools to the PATH variable:

C:\>set PATH=%PATH%;C:\Amazon RDS\CLI

Creating a Database Instance

We next focused on creating an Extra Large database instance, with an allocated storage of 5GB:

C:\>rds-create-db-instance --engine MySQL5.1 / 
--master-username root --master-user-password mypass
--db-name WebyogTestData --db-instance-identifier webyogtestinstance /
--allocated-storage 5 --db-instance-class db.m1.xlarge –-header

DBINSTANCE  DBInstanceId        Class         Engine    Storage  Master Username
Status    Backup Retention
DBINSTANCE  webyogtestinstance  db.m1.xlarge  mysql5.1  5        root
creating  1
SECGROUP  Name     Status
SECGROUP  default  active
PARAMGRP  Group Name        Apply Status
PARAMGRP  default.mysql5.1  in-sync

The rds-decribe-db-instances command displays all of the running instances:

DBINSTANCE  webyogtestinstance  2009-11-06T08:40:52.571Z  db.m1.xlarge  mysql5.1
5   root  available 3306  us-east-1d  1
SECGROUP  default  active
PARAMGRP  default.mysql5.1  in-sync

That was it. Our database was up and running.

Connecting SQLyog/MONyog to Amazon RDS

Here's the best part about Amazon RDS: It has native MySQL 5.1 support. This means that you can use our favorite MySQL GUI tool to connect to an Amazon RDS database instance.

SQLyog Settings for RDS
SQLyog settings for RDS

We entered the master username and password, the same one given when we created the DB instance. For the host address, we used It's shown in the output of the rds-describe-db-instances command.

We then clicked on the Test Connection button. It connected successfully, as you can see below. Notice that SQLyog reports as having connected to MySQL 5.1.38-log.

Success connecting to Amazon RDS
Success connecting to Amazon RDS

Setting up Monyog was as simple at this point. Below are screenshots of how the Amazon RDS instance looks from Monyog.

MONyog displaying Amazon RDS DB stats
MONyog displaying Amazon RDS DB stats

As you can see here, all of the usual monitoring tools from Monyog work just find when interfaced with a database instance from Amazon RDS. While it might be a bit of trouble to get things started with Amazon RDS, once you do, you can retreat back to Monyog and relax as you control your databases.

MONyog displaying the InnoDB Cache stats
MONyog displaying the InnoDB Cache stats


Periodically, the Amazon RDS system performs some maintenance of database instances. This ensures that your server is running smoothly. This also translates into a 4-hour down time period on a weekly basis. Within a weekly 4-hour user-definable window (i.e., the maintenance window), Amazon's management system may start back-ups or roll out patches for the MySQL server. This may, however, result in a certain amount of downtime of your database instance. So, be prepared for that.


Amazon RDS is just a MySQL 5.1 instance running on an Amazon EC2 platform, but with all of the advantages of EC2. You can scale your server to use up to 68 GB of memory, 26 ECUs, and 1 TB of persistent storage. However, Amazon RDS doesn't support replication, yet.

The release of Amazon RDS indicates a pattern. In 2008 when it became clear that Microsoft would announce a Windows-based Cloud, Amazon jumped in and announced support for Windows-based EC2 instances. And now, Amazon has done it again, this time with RDS in response to Microsoft's SQL Azure. Competition with Microsoft seems to drive Amazon much more than requests from its users.

For us at Webyog this is an exciting development. We believe that our products (SQLyog and MONyog) are very fit for the Cloud.  Our products are much more fit than the console-based tools that most advanced users still seem to use.  We will now start checking our programs in detail with this. So far we've found no problems.

Want to Know More?

Read more about Amazon RDS froom their website.

Amazon RDS Functionality.

Pricing plans for Amazon RDS.

Sign up for Amazon RDS.