Relational databases offer organizations quicker insights into data affecting business output. They offer a lot of advantages, but there are also downsides.
Regular maintenance and the complexity of finding the right Relational Database Management Software (RDBMS) can be stressful, especially because many of these solutions use a lot of on-premise IT infrastructure.
Thankfully, there’s Amazon’s Relational Database Service (RDS)—an Amazon Web Service solution for effective relational database management that requires a less hands-on approach.
RDS helps you outsource your database management to a third party ( i.e., AWS), garner more storage space for your data needs, and only pay for what you use.
This article walks you through AWS RDS, covering how it works, how to get the most from it, and details some of its limitations.
What is Amazon Relational Database Services (AWS)?
Amazon RDS is an Amazon service for assembling, storing, and maintaining relational databases in the cloud.
RDS helps you bypass the need for Relational Database Management Software(RDBMS) and outsource the stress of maintaining and securing your database in a virtual environment.
From the AWS management console, you create Database(DB) instances, isolated environments where users store and manage their related databases.
The result is enhanced database performance at a lower cost.
Use cases for Amazon RDS
There are many ways you can use RDS within an organization, some of which include:
- Web-based applications
- SaaS applications
- Business Analytics
- Medical and banking compliance
How does RDS work?
RDS uses SQL queries and other components to store, manage, monitor, and safeguard relational databases in the cloud.
These additional components behind the smooth running of the Amazon RDS include database selection and management, security features, and scalability options.
Database engine selection
Database engines are the starting point for your RDS implementation and the RDS version of an RDBMS.
RDS provides a mix of commercial and open-source database engines. These include:
- PostgreSQL
- Microsoft SQL server
- RDS for Oracle
- RDS for MariaDB
- RDS for MySQL
- Amazon Aurora (compatible with MySQL and PostgreSQL)
All these engines work in different ways, and you’ll have to choose an engine version that aligns with your database needs.
Features to look out for when deciding on an RDS DB engine include:
- Cost: This covers instance size, storage, data transfer, and backup costs.
- Scalability: Determine if the engine type allows you to scale horizontally or vertically when necessary.
- Data volume: Consider the size of data you need to store over time, its potential to grow, and if the engine can handle the data growth.
- Performance: Confirm its throughput, latency, and cloud deployment capacity.
For example, the Oracle engine is more of a commercial engine, making it an ideal choice if you have a larger volume of data to deal with. The MySQL engine is the more cost-efficient option that offers scalability and high availability, and the MariaDB is great for easier and faster cloud deployments.
Managed environment
RDS reduces the bulk of the work of a database administrator by providing an environment that automatically handles tasks like data backup, patching, and repair. Taking these tasks away from the administrator gives them more time to focus on setting up and running DB instances and building applications.
Configuration and customization
You can set up Amazon RDS to suit your specific database needs with its configuration and customization features. These features allow you to set parameters for RDS database instances, select your instance type (general purpose and memory-optimized instance types), and opt for any storage type based on your database workload.
For instance, you’ll need the memory-optimized instance type for working with large databases and applications that need lots of memory and low latency.
Data storage and backups
Amazon RDS measures data using the input/output operation per second (IOPS) metric and stores it on a solid-state drive (SSD). It comes with three storage types:
- General Purpose SSD with up to 3000 IOPS capacity
- Provisioned IOPS SSD with up to 256,000 IOPS
- Magnetic storage
It also allows you to stop and restart work on an RDS instance at any point through data backup and recovery.
High availability and scalability
RDS provides relational database deployments across three availability zones (AZ) and two readable standby options to ensure service availability, especially during backups and database instance failures. This means shorter time to recover from failover, fewer chances of data loss, and ease of scaling down or scaling up workload.
This feature varies according to your choice of RDS DB engine, but the two readable standby options are available on the RDS Aurora PostgreSQL and MySQL engines.
Security features
RDS has different ways of preserving the integrity of its databases. One way is by controlling access to stored databases and preventing interference from malicious agents.
The built-in Identity and Access Management (IAM) feature also helps control access levels, distinguishing the duties of a developer from those of an administrator.
Another option is encryption to safeguard data, including backups and snapshots. You can also host your database instances in a private cloud known as Amazon virtual private cloud (VPC), which isolates your network while allowing you to connect with your company’s IT infrastructure.
Monitoring and management
You’ll need to monitor many metrics to get the most out of this service. With Amazon Cloudwatch (console or API), you can monitor allocated storage, DB instances, and option groups, amongst other metrics.
RDS also notifies you of when it will perform routine maintenance on different parts of your DB instances within a stipulated time frame.
RDS vs. EC2: Understanding the differences
Amazon Elastic Cloud Compute (EC2) is another AWS solution that can help with database management. These are easy to mix up; some organizations end up using EC2 even when RDS is the ideal option.
Amazon RDS and EC2 operate on two different cloud computing models. To be more precise, RDS is a Platform as a Service (PaaS) and a database as a service (DBaaS), while EC2 is an infrastructure as a service (IaaS).
Here’s a breakdown of how both products differ from each other:
Managed service vs. Infrastructure as a Service (IaaS)
Unlike RDS, which is limited to relational databases, EC2 allows direct access to virtual servers to launch applications. So, with Amazon EC2, you get a more comprehensive solution to your cloud computing needs, like provisioning different parts of your IT infrastructure.
Database engine options
RDS provides six different database engines to help implement a relational database. However, there are no limitations on database engine types and versions with EC2. You also get five instance types with EC2 which include:
- General purpose instance type
- Compute-optimized instances
- Memory-optimized instances
- Accelerated computing instances
- Storage optimized instances
To use a database on an EC2 instance, you’ll have to connect it through the EC2 console, RDS console, or do a manual configuration using security groups.
EC2 has more than 750 instances, which is higher than RDS’ due to its higher cloud computing capability. So, it’s a more comprehensive solution for your cloud computing needs like data processing, content delivery, web hosting, and application development and testing.
Scalability
With both products, you have control of both vertical and horizontal scaling, where you can either increase the CPU capability on the platform or add more storage if your workload increases.
Cost structure
AWS is clear on how pricing works on both platforms because apart from the available free tier, pricing for RDS is in tiers based on the following factors:
- Instance types: RDS prices and instances go according to their workload category, which includes on-demand instances (which bills you per hour of use) and reserved instances (which provide a subsidized cost for a one- or three-year period)
- Storage: RDS storage types come at different costs for their usage.
- Engine type: The different database engines available on RDS have different costs attached to them.
- Operational expenses: These include data transfer costs, extended support on using select database engines, and RDS deployments, which add up to the overall cost of using Amazon RDS.
EC2 also allows you to pay for only what you use through per-second billing, saving plans, on-demand, and reserved instances.
Note: Initially, you can use the pricing calculator to estimate the cost of any service based on the features you need. Afterward, you can assign cost allocation tags to any AWS resource you use and set up your AWS cost and usage report to get a breakdown of your investment in Amazon’s cloud computing services.
Why use RDS instead of EC2?
If your goal is relational database management, you’re better off with RDS than EC2 for the following reasons:
Simplified management
The biggest win for RDS over EC2 is its ease of use. There’s less need for constant check-ins or multiple employees trying to maintain the database since RDS handles such administrative tasks.
Less administrative overhead
Since RDS is a managed service, AWS takes charge of most of the responsibility in handling your databases. But EC2 operates differently and requires more attention from you, the user, as the tool needs to provision the entire IT infrastructure.
Automated high availability
RDS provides failover support for its users by automatically switching to a standby database instance in a different Availability Zone. This minimizes data loss during downtimes and enhances the durability of its databases. On EC2, this feature is not automatic—you’ll have to set it up yourself.
Automated backups
RDS provides automated daily backups and the ability to retain backups for a specified period, making it easier to recover data in case of accidental deletions or data corruption.
Limitations of RDS
Although RDS has a lot to offer, you should be aware of some downsides to the platform. These include:
Limited database customization and control
RDS doesn’t grant users enough flexibility in setting up the databases. For instance, there’s limited opportunity for installing packages that help launch applications.
Plus, there are restrictions on configuring databases and even naming database instances.
Performance constraints
You can’t always count on RDS for optimal performance. Functions like scaling operations and patching create downtime that can be hard to resolve automatically.
Cost
Overall, RDS is a costly solution compared to other relational database solutions. Maintenance costs (including schema design) and data transfer requirements add to these costs.
Hence, it’s best suited for larger organizations. There are, however, methods for cost optimization by using reserved instances, opting for Amazon Aurora, turning off multi-AZ deployment, and using a serverless DB.
Limited direct server access
RDS does not grant users direct access to its servers.
This limits how much database administrators can achieve on their own without support from the AWS support team, especially in getting to the root cause of a database issue.
Reduced feature set
DBs on RDS offer lesser control to the user since most functions are automated based on how AWS designed the platform.
On the other hand, EC2 databases require your input for backups and scaling features. You can install a DB engine and control the database server and operating system.
ProsperOps: Your solution for streamlined cloud cost control
If you’re considering migrating to Amazon RDS, figuring out how to cut down on the cloud cost should be top of your list.
This is where you’ll need ProsperOps to help with AWS cost management. ProsperOps uses automation to help you save and get more value from your cloud solution.
Book a demo with the ProsperOps team today and see how our solutions can help your business optimize your cloud spend.
