With the advent of Cloud computing solutions, the need to leverage Big Data services has seen a meteoric surge. Organizations are migrating from On-premise databases to the Cloud for secured storage and better information accessibility through shared Internet connections. The proliferation of Cloud-based Relational databases allows companies to get started quickly and eliminates tedious database management activities. One of the most popular Cloud-based Relational databases is Amazon RDS, aka Amazon Relational Database Service. With Amazon RDS, organizations can set up, operate, and scale with just a few clicks. This article will help you understand what Amazon RDS is and what are its advantages.
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What is Relational Database
A Relational Database uses tables with columns and rows to organize data. While each row in a Relational Database represents a record, each column represents a piece of information about that record. As a result, it is similar to a spreadsheet but has more features as it creates relations among several disparate data. This makes Relational Database systems easier to scale while maintaining data integrity. Data stored in a Relational Database can not only be cross-referenced between multiple databases through relationships but also allows multiple users to access information simultaneously.
The concept of Relational Databases dates back to 1970, arising out of the need to collate and hold data in a practical and streamlined manner. Each piece of data in a Relational Database uses an identifier called a unique key. The problem with this system arises when a database with many tables and thousands of records with unique identifiers soon gets complex. This can lead to issues in terms of performance, accessibility, scalability, security, and IT infrastructure. To offset such bottlenecks, companies started embracing Database-as-a-Service (DBaaS) like Amazon RDS.
The following image shows a sample Relational Database:
What is Amazon RDS
Amazon RDS is a Relational Database available through the AWS Cloud Computing Services platform. It helps users seamlessly handle database management tasks, like migration, patching, backup, and recovery. The Amazon Relational Database Service (RDS) was launched in October 2009 and is designed to host Relational Database instances in the Cloud to support applications’ operations and provide data for analytics, reporting, and business dashboards.
A database instance is a unique environment created in the AWS Cloud. It can contain several databases, and when users update the settings of an instance, they are automatically applied to all of the databases included. Amazon considers database instances to be the basic building block of the Amazon Relational Database Service (RDS). Users can easily create and modify a database instance. This is achieved by utilizing the AWS Management Console, AWS Command Line Interface (AWS CLI), or Amazon RDS API calls.
Thanks to Amazon RDS subscription options, users do not have to buy any Server or install any database software in it. They only needed to set up specific initial settings, such as memory and CPU capacity allocation. It allows users to concentrate on developing applications and ensuring that they have the required performance and security. Amazon Relational Database Service (RDS) can back up the user database, preserve the backups for a user-defined retention period, and enables point-in-time recovery.
Users can also quickly migrate or replicate existing databases to Amazon Relational Database Service (RDS) using the AWS Database Migration Service. However, it is important to note that from a configuration and execution standpoint, migrating in and out of RDS with zero downtime can be difficult. Some of the standard Amazon RDS services/features are as follows:
- Monitoring and Metrics.
- Automatic Software Patching.
- Amazon Virtual Private Cloud (VPC) access (encrypted IPsec VPN).
- Automatic backups and host replacements.
- Software updates for the Database engine.
- Easy scaling for storage and compute or Storage Optimization.
- Multi-Availability Zone with synchronous replication.
- Cross-Region Read Replicas.
- Automatic minor update of the database.
More information about Amazon Relational Database Service (RDS) can be found here.
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Let’s look at Some Salient Features of Hevo:
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- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
Understanding Amazon RDS Database Engines
Every database instance runs a database engine. The Relational Databases supported by Amazon Relational Database Service (RDS) include MySQL, PostgreSQL, MariaDB, Oracle, Microsoft SQL Server, and Amazon Aurora. While MySQL, PostgreSQL, and MariaDB are Open-source Database technologies, Oracle Database and Microsoft SQL Server are owned and developed by Oracle and Microsoft, respectively. The final database, Amazon Aurora, is an AWS-exclusive database. This is a fully managed Relational Database engine that is compatible with MySQL and PostgreSQL.
Among the available options, the Open-source database engines are the most economical. Oracle and Microsoft SQL Server engines are the most expensive in the lot because their Amazon RDS service comes with their database licenses included.
Understanding the Supported Storage Types
On the basis of performance characteristics and prices, Amazon Relational Database Service (RDS) supports three storage types of the database instance which are as follows:
- General Purpose SSD: Also known as gp2, General Purpose SSD provides low-cost storage suitable for a wide range of applications and delivers single-digit millisecond latencies. It gives a baseline of 3 IOPS for every provisioned GB. They also have the ability to burst to 3,000 IOPS for extended periods of time. Bursting implies that the storage can respond with higher IOPS than the baseline, but only for short periods.
- Provisioned IOPS SSD: Also known as io1, Provisioned IOPS SSD storage is optimized for I/O-intensive applications, such as database workloads, that require low I/O latency and consistent I/O throughput. Here, users can specify their desired IOPS rate, up to 40,000 IOPS for each RDS instance.
- Magnetic Storage: Also known as Standard Storage, Magnetic storage is offered by Amazon RDS for backward compatibility.
More information about Storage types can be found here.
Benefits of using Amazon RDS
The benefits of using Amazon RDS are as follows:
- Scalability: Amazon RDS offers two types of Automatic Scaling, i.e., Horizontal (adding more machines) and Vertical (adding more resources). Amazon Relational Database Service (RDS) allows users to scale their infrastructure up or down with little to no downtime through only a few clicks or API calls. One can scale up to a maximum of 32 vCPUs and 244 GiB with Amazon Relational Database Service (RDS).
- High Durability and Availability: When storing data on the Cloud, users must be able to access it whenever and wherever they want. The Multi-Availability Zone feature of Amazon Relational Database Service (RDS) allows increased availability and durability of databases across the globe. Multi-Availability Zone automatically provisions and maintains a synchronous redundant replica of user data in a separate location. It’s in standby mode and doesn’t respond to queries. But in the event of an Availability Zone outage or internal hardware or network outage, Amazon Relational Database Service (RDS) will immediately transition from the primary instance to the available backup replica. As a result, the impact on availability is limited to the time it takes for automated failover to complete.
- Ease of Administration: With Amazon Relational Database Service (RDS), AWS handles and automates configuration, management, maintenance, and security. To access the features of a production-ready Relational Database in minutes, one simply has to use the Amazon RDS Management Console, the AWS RDS Command-Line Interface, or simple API calls.
- Data Security: Frequent patching and security audits optimize the overall security of Amazon Relational Database Service (RDS). Besides, users can safeguard their databases by placing them in Amazon Virtual Private Cloud (VPC). They can isolate the database instances using VPC while connecting to existing IT infrastructure using an industry-standard secured IPsec VPN. Amazon Relational Database Service (RDS) also offers encryption at rest and in transit. With the former, Amazon Relational Database Service (RDS) users can encrypt databases using keys, which are maintained by Amazon RDS’s KMS (Key Management Service). In this, the underlying data storage is secured at rest, along with its automatic backups, read replicas, and snapshots. And in-transit encryption secures communications between database instances and applications using SSL/TLS, installed when an instance is provisioned. Amazon Relational Database Service (RDS) security is further complemented with AWS’s extensive security measures like Identity and Access Management (IAM) to aid with the management of access privileges.
- Better Costs: Here, users only need to pay for the RDS features they use and the number of instances that they require without worrying about up-front costs. Hence, it is possible that they may be able to get away with free services for up to a year. For the period of 12 months, AWS provides users with a free tier of Amazon RDS use of 750 hours per month with 20 GB of storage for anyone who wants to test out the service.
Apart from the above, Amazon RDS offers numerous benefits. For instance, it allows storage of up to 1 TB per database instance. With Amazon Relational Database Service (RDS), users can not only automate data backup but also create manual snapshots of the databases. Such backup methods come in handy for restoring a specific database using Amazon’s RDS’s dependable and rapid restore process.
Amazon RDS Pricing
Amazon allows users to choose between the two modes of pricing:
- On-demand DB instances: Users pay by the hour for the DB instance hours used.
- Reserved DB instances: Users reserve a DB instance for a one-year or three-year term and receive a significant discount.
The billing also depends on factors like storage capacity assigned to a DB instance, the total number of I/O requests per month, rate of provisioned IOPS, mode of data transfer, and more.
More information about Amazon Relational Database Service (RDS) can be found here.
Undoubtedly, Amazon RDS has relieved the hassles and complexities of dealing with Relational Database Management Systems. Thanks to its wide array of features and long-term benefits, Amazon Relational Database Service (RDS) ushers in a new era of Cloud Database-as-a-Service (DBaaS) to help organizations gain operational resilience.
Most database migration tasks, if done manually, require immense engineering bandwidth and resources for the development and maintenance of Data Pipelines. Hence, businesses can instead use existing automated No-code platforms like Hevo.
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