Amazon Relational database

Amazon Relational Database Service (RDS)

Amazon RDS is a web service that makes it easier to set up, operate, and scale a relational database in the AWS Cloud. It provides cost-efficient, resizeable capacity for an industry-standard relational database and manages common database administration tasks.

  • It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. 
  • AWS clients can have automated backups or manually create their own backup snapshot.
  • They can get high availability with a primary instance and a synchronous secondary instance that they 
    can fail over to when problems occur.
  • RDS power all types of applications from social media apps, e-commerce websites, and blogs to complex enterprise applications.
  • Commonly used relational database software packages include MySQL, PostgreSQL, Microsoft SQL Server, and Oracle

RDS Benefits

Scalability:- AWS customers can scale their database’s compute and storage resources to handle a growing amount of work by adding resources to the system. Many Amazon RDS engine types allow customers to launch one or more Read Replicas to offload read traffic from their primary database instance.

Security:- Amazon RDS makes it easy to control network access to customers database let them run their database instances in Amazon Virtual Private Cloud (Amazon VPC),

  • This enables customers to isolate their database instances, and to connect to their existing IT infrastructure through encrypted IPsec VPN.
  • Many Amazon RDS engine types offer encryption at rest and encryption in transit.

Easy to administer:- AWS clients can use the Amazon RDS Management Console, the AWS RDS Command-Line Interface, or simple API calls to access the capabilities of a production-ready relational database in minutes.

  • Amazon RDS is a service that simplifies the setup, operations, and scaling of a relational database on AWS.
  • No need for infrastructure provisioning, and no need for installing and maintaining database software.

Availability and durability:- Amazon RDS runs on the same highly reliable infrastructure used by other Amazon Web Services. When customers provision a Multi-Availability Zone database Instance, Amazon RDS synchronously replicates the data to a standby instance in a different Availability Zone (AZ). 

Relational databases Concept

Amazon Machine Image

Amazon Machine Image

SQL commands are divided into categories, the two main being

  1. Data Manipulation Language (DML) commands:- The DML commands deal with the manipulation of the data such as inserting, updating, and deleting.
  2. Data Definition Language (DDL) commands:- DDL deals with creating, altering, and dropping (deleting) the table structure.

A data warehouse is a central repository for data that can come from one or more sources. This data repository is often a specialized type of relational database that can be used for reporting and analysis via OLAP. Organizations typically use data warehouses to compile reports and search the database using highly complex queries.

Amazon RDS is often used for OLTP workloads, but it can also be used for OLAP. Amazon Redshift is a high-performance data warehouse designed specifically for OLAP use cases. It is also common to combine Amazon RDS with Amazon Redshift in the same application and periodically extract recent transactions and load them into a reporting database.

Relational databases provide a common interface that lets customers read and write from the database using commands or queries written using Structured Query Language (SQL). A relational database consists of one or more tables, and a table consists of columns and rows. While the database column contains a specific attribute of the record, such as a person’s name, address, and telephone number, A database row comprises an individual record, such as the details about a student who attends a school.

  • A primary key uniquely identifies a record in the table, and the unique column containing the unique record is called the primary key.A primary key uniquely identifies a record in the table, and the unique column containing the unique record is called the primary key.
  • A foreign keyis a field in one table that uniquely identifies rows in another table or the same table. The foreign key is defined in a second table, but it refers to the primary key or a unique key in the first table.
  • Each attribute is assigned a data type such as text, number, or date, and the database engine will reject invalid inputs.
  • Relational databases follow certain rules to ensure data integrity and accessibility of data. 
    1. RDBMS table should be distinct. For most RDBMSs, a customers can specify that duplicate rows are not allowed, in which case the RDBMS prevents duplicates. 
    2. Column values must not have repeating groups or arrays.
    3. In an RDBMS, customers can use the value of NULL  for the unknown column, which simply means the data is not available. Note that NULL does not mean a missing value or zero.
  • A relational database can be categorized as either; 
    1. Online Transaction Processing (OLTP) database system refers to transaction oriented applications that are frequently writing and changing data such as, data entry and e-commerce; or 
    2. Online Analytical Processing (OLAP) database system is typically the domain of data warehouses and refers to reporting or analyzing large data sets. Large applications often have a mix of both OLTP and OLAP databases.

RDS Features

The  type of instance that client specify determines the hardware of the host computer used for their instance. Each instance type offers different compute, memory, and storage capabilities and are grouped in instance families based on these capabilities. Each instance type provides higher or lower minimum performance from a shared resource.

RDS Security

Amazon RDS allows customers to encrypt their databases using keys that manage through AWS Key Management Service (KMS). On a database instance running with Amazon RDS encryption, data stored at rest in the underlying storage is encrypted, as are its automated backups, read replicas, and snapshots.

AWS customers can isolate their database in their own virtual network and connect to their on-premises IT infrastructure using industry-standard encrypted IPsec VPNs. 

Amazon RDS is integrated with AWS Identity and Access Management (IAM) and provides its customers the ability to control the actions that they AWS IAM users and groups can take on specific Amazon RDS resources, from database instances through snapshots, parameter groups, and option groups. 

Amazon RDS provides Amazon CloudWatch metrics for customers database instances at no additional charge.

  • Aws customers can use the RDS Management Console to view key operational metrics, including compute/memory/storage capacity utilization, I/O activity, and instance connections. 
  • Amazon RDS integrates with AWS Config to support compliance and enhance security by recording and auditing changes to the configuration of customers DB instance including parameter groups, subnet groups, snapshots, security groups and event subscriptions.

Amazon RDS Proxy

Amazon RDS Proxy is a fully managed, highly available database proxy for Amazon Relational Database Service (RDS) that makes applications more scalable, more resilient to database failures, and more secure. Amazon RDS Proxy can be enabled for most applications with no code change, and customers don’t need to provision or manage any additional infrastructure.

  • Amazon RDS Proxy supports Amazon RDS for MySQL and Amazon Aurora with MySQL compatibility. 
  • Amazon RDS Proxy allows applications to pool and share connections established with the database, improving database efficiency and application scalability.
  • Using RDS Proxy database credentials, authentication, and access customers can manage through integration with AWS Secrets Manager and AWS Identity and Access Management (IAM).
    • Pool and share database connections for improved application scaling by establishing connections to customers RDS database instances.
    • Increase application availability and reduce database failover times.
    • Manage application data security with database access controls.
    • Amazon RDS Proxy is a fully managed database proxy feature for Amazon RDS, giving you all the benefits of a database proxy without requiring additional burden of patching and managing your own proxy server
    • Customers can build serverless applications that are more scalable and more available because they use their relational databases more efficiently.
    • SaaS or eCommerce applications often keep a large number of database connections open to ensure quick user response times, although only a fraction of these open connections may get actively used at a given moment.

Performance

Amazon RDS database instances are pre-configured with parameters and settings appropriate for the engine and class you have selected.

  • Amazon RDS will make sure that the relational database software powering its clients deployment stays up-to-date with the latest patches. So that they can exert optional control over when and if their database instance is patched.

While the purpose of Amazon RDS General Purpose Storage  is to deliver a consistent baseline of 3 IOPS per provisioned GB and the ability to burst up to 3,000 IOPS above the baseline, Amazon RDS Provisioned IOPS Storage designed to deliver fast, predictable, and consistent I/O performance. 

  • Read Replicas elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads. 
  • Although the Amazon Aurora engine will automatically grow the size of AWS clients database volume up to a maximum of 64 TB; MySQL, MariaDB, Oracle, and PostgreSQL engines allow them to scale up to 32 TB of storage. Those who is using SQL Server  get a supports up to 16 TB.

Customers can scale the compute and memory resources powering their deployment up or down, up to a maximum of 32 vCPUs and 244 GiB of RAM.    

The Amazon RDS automated backup enables its customers point-in-time recovery for their database instance.

  • Database snapshots are user-initiated backups of customers instance stored in Amazon S3 that are kept until they explicitly delete them.
  • Amazon RDS Multi-AZ deployments provide enhanced availability and durability for database instances, making them a natural fit for production database workloads.
  • Amazon RDS will automatically replace the compute instance powering customers deployment in the event of a hardware failure.

Amazon RDS on Outposts

Amazon RDS on AWS Outposts enable customers to deploy fully managed database instances in their on-premises environments. It is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience.

  • AWS Outposts is a fully managed service that extends AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience. 
  • Amazon RDS on Outposts provision, monitor, and operate relational databases on premises, including for low latency workloads that need to remain close to on-premises data and applications.
  • RDS on Outposts automates administrative functions for on-premises databases, including provisioning, operating system and database patching, backup, point-in-time restore, compute scaling, instance health monitoring, and failover.
  • Customers can manage RDS databases both in the cloud and on premises using the same AWS Management Console, APIs, and CLI. 
  • Amazon RDS on Outposts monitors to detect unhealthy database instances and automatically recovers them using the same storage volume, ensuring availability protection for your on-premises databases. 
  • Customers can manage RDS databases both in the cloud and on Outposts using the same AWS Management Console, APIs.
    • They can manage a hybrid cloud database fleet with the unified RDS interface and use the AWS Region for backup and restore.

Amazon RDS DB Instances

A DB instance is an isolated database environment running in the cloud. It is the basic building block of Amazon RDS. A DB instance can contain multiple user-created databases, and can be accessed using the same client tools and applications you might use to access a standalone database instance. DB instances are simple to create and modify with the Amazon AWS command line tools, Amazon RDS API operations, or the AWS Management Console. 

  • Each DB instance has a DB instance identifier. This customer-supplied name uniquely identifies the DB instance when interacting with the Amazon RDS API and AWS CLI commands. The DB instance identifier must be unique for that customer in an AWS Region.
  • Each DB instance supports a database engine. Amazon RDS currently supports MySQL, MariaDB, PostgreSQL, Oracle, Microsoft SQL Server, and Amazon Aurora database engines.
  • A DB instance can host multiple databases, or a single Oracle database with multiple schemas. The database name value depends on the database engine.
  • Amazon RDS creates a master user account for clients DB instance as part of the creation process. This master user has permissions to create databases and to perform create, delete, select, update, and insert operations on tables the master user creates. Thus, customers need to set the master user password when they create a DB instance.
AWS Regions and Availability Zones

AWS Regions and Availability Zones

Terminology for DB Instance Classes

vCPU 

The number of virtual central processing units (CPUs). A virtual CPU is a unit of capacity that AWS customers can use to compare DB instance classes. Instead of purchasing or leasing a particular processor to use for several months or years. The goal is to make a consistent and specific amount of CPU capacity available, within the limits of the actual underlying hardware.

Memory (GiB) 

The RAM, in gibibytes, allocated to the DB instance. There is often a consistent ratio between memory and vCPU. As an example, take the db.r4 instance class, which has a memory to vCPU ratio similar to the db.r5 instance class. However, for most use cases the db.r5 instance class provides better, more consistent performance than the db.r4 instance class.

EBS-Optimized 

The DB instance uses an optimized configuration stack and provides additional, dedicated capacity for I/O. This optimization provides the best performance by minimizing contention between I/O and other traffic from your instance. For more information about Amazon EBS–optimized instances, see Amazon EBS–Optimized Instances in the Amazon EC2 User Guide for Linux Instances.

ECU 

The relative measure of the integer processing power of an Amazon EC2 instance. To make it easy for developers to compare CPU capacity between different instance classes, we have defined an Amazon EC2 Compute Unit. The amount of CPU that is allocated to a particular instance is expressed in terms of these EC2 Compute Units. One ECU currently provides CPU capacity equivalent to a 1.0–1.2 GHz 2007 Opteron or 2007 Xeon processor.

VPC Only

The instance class is supported only for DB instances that are in a VPC based on the Amazon VPC service. In some cases, AWS customers might want to use an instance class that requires a VPC but their current DB instance isn’t in a VPC. In these cases, start by moving customer’s DB instance into a VPC. For more information, see Moving a DB Instance Not in a VPC into a VPC.

Max. Bandwidth (Mbps) 

The maximum bandwidth in megabits per second. Divide by 8 to get the expected throughput in megabytes per second.

General Purpose SSD (gp2) volumes for Amazon RDS DB instances have a throughput limit of 250 MiB/s in most cases. However, the throughput limit can vary depending on volume size. For more information, see Amazon EBS Volume Types in the Amazon EC2 User Guide for Linux Instances. For information on estimating bandwidth for gp2 storage, see General Purpose SSD Storage.

Amazon RDS Storage Types

Amazon RDS provides three storage types: General Purpose SSD (also known as gp2), Provisioned IOPS SSD (also known as io1), and magnetic. They differ in performance characteristics and price, which means users can tailor their storage performance and cost to the needs of their database workload. AWS customers can create MySQL, MariaDB, Oracle, and PostgreSQL RDS DB instances with up to 64 TiB of storage. They can create SQL Server RDS DB instances with up to 16 TiB of storage. For this amount of storage, use the Provisioned IOPS SSD and General Purpose SSD storage types.

Provisioned IOPS 

Provisioned IOPS storage is designed to meet the needs of I/O-intensive workloads, particularly database workloads, that require low I/O latency and consistent I/O throughput. For a production application that requires fast and consistent I/O performance, Provisioned IOPS (input/output operations per second) storage is best suited. Provisioned IOPS storage is a storage type that delivers predictable performance, and consistently low latency. Provisioned IOPS storage is optimized for online transaction processing (OLTP) workloads that have consistent performance requirements. Provisioned IOPS helps performance tuning of these workloads.

AWS customers can use Provisioned IOPS SSD storage with read replicas for MySQL, MariaDB or PostgreSQL. The type of storage for a read replica is independent of that on the master DB instance. For example, you might use General Purpose SSD for read replicas with a master DB instance that uses Provisioned IOPS SSD storage to reduce costs. However, your read replica’s performance in this case might differ from that of a configuration where both the master DB instance and the read replicas use Provisioned IOPS SSD storage.

Provisioned IOPS SSD storage provides a way to reserve I/O capacity by specifying IOPS. However, as with any other system capacity attribute, its maximum throughput under load is constrained by the resource that is consumed first. That resource might be network bandwidth, CPU, memory, or database internal resources.

General Purpose SSD

General Purpose SSD volumes offer cost-effective storage that is ideal for a broad range of workloads. These volumes deliver single-digit millisecond latencies and the ability to burst to 3,000 IOPS for extended periods of time. Baseline performance for these volumes is determined by the volume’s size. The following are the storage size ranges for General Purpose SSD DB instances:

  • MariaDB, MySQL, Oracle, and PostgreSQL database instances: 20 GiB–64 TiB
  • SQL Server for Enterprise, Standard, Web, and Express editions: 20 GiB–16 TiB

Many workloads never deplete the burst balance, making General Purpose SSD an ideal storage choice for many workloads. However, some workloads can exhaust the 3,000 IOPS burst storage credit balance, so that customers plan their storage capacity to meet the needs of the workloads.

General Purpose SSD storage performance is governed by volume size, which dictates the base performance level of the volume and how quickly it accumulates I/O credits. Larger volumes have higher base performance levels and accumulate I/O credits faster. I/O credits represent the available bandwidth that the General Purpose SSD storage can use to burst large amounts of I/O when more than the base level of performance is needed. The more I/O credits the customer storage has for I/O, the more time it can burst beyond its base performance level and the better it performs when the workload requires more performance.

 

Magnetic 

Amazon RDS also supports magnetic storage for backward compatibility. It is AWS recommendation that clients to use General Purpose SSD or Provisioned IOPS for any new storage needs. The maximum amount of storage allowed for DB instances on magnetic storage is less than that of the other storage types. The following are some limitations for magnetic storage:

  • Doesn’t allow customers to scale storage when using the SQL Server database engine.
  • Doesn’t support storage autoscaling.
  • Doesn’t support elastic volumes.
  • Limited to a maximum size of 3 TiB.
  • Limited to a maximum of 1,000 IOPS.

Database Engines

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. Amazon RDS is available on several database instance types – optimized for memory, performance or I/O – and provides you with six familiar database engines to choose from, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server. You can use the AWS Database Migration Service to easily migrate or replicate your existing databases to Amazon RDS

Oracle®

Oracle® Database is a relational database management system developed by Oracle. Amazon RDS makes it easy to set up, operate, and scale Oracle Database deployments in the cloud. With Amazon RDS, you can deploy multiple editions of Oracle Database in minutes with cost-efficient and re-sizable hardware capacity. Amazon RDS frees you up to focus on application development by managing time-consuming database administration tasks including provisioning, backups, software patching, monitoring, and hardware scaling.

  • Amazon RDS for Oracle DB Instances can be provisioned with either standard storage or Provisioned IOPS storage. 
  • Amazon RDS Provisioned IOPS is a storage option designed to deliver fast, predictable, and consistent I/O performance, and is optimized for I/O-intensive, transactional (OLTP) database workloads. 
  • In addition to that, the easy to use replication enhanced availability and reliability for production workloads. Using the Multi-AZ deployment option  customers can run mission critical workloads with high availability and built-in automated fail-over from their primary database to a synchronously replicated secondary database in case of a failure. 

MariaDB

MariaDB is a popular open source relational database created by the original developers of MySQL. Amazon RDS makes it easy to set up, operate, and scale MariaDB server deployments in the cloud. With Amazon RDS, AWS clients can deploy scalable MariaDB cloud databases in minutes with cost-efficient and resizable hardware capacity. Amazon RDS automatically patches the database software and backs up customers database, storing the backups for a retention period that was defined and enables point-in-time recovery. 

Amazon RDS for MariaDB DB Instances can be provisioned with General Purpose (SSD) storage or Provisioned IOPS (SSD) storage. Provisioned IOPS (SSD) is a high performance storage option designed to deliver fast, predictable, and consistent performance for I/O intensive transactional database workloads. Amazon RDS for MariaDB eenhand the availability and reliability of customers’ productions workloads by automating replication across AWS availability zones.

  • Amazon RDS for MariaDB deployments are pre-configured with a set of parameters and settings appropriate for the Database Instance class the customers have selected, which makes it easy for them to launch a MariaDB Instance and connect their application within minutes, without having to do any configuration.
  • Amazon RDS for MariaDB deployments are pre-configured with a set of parameters and settings appropriate for the Database Instance class selected, that makes it easy to launch the MariaDB Instance and connect customers applications within minutes.

SQL Server

SQL Server is a relational database management system developed by Microsoft, and Amazon RDS for SQL Server is a managed service that is designed for developers who require the features and capabilities of SQL Server for building a new application. AWS clients can also move existing applications that utilize SQL Server to Amazon RDS without having to rewrite the application completely. Using Amazon RDS, AWS customers can deploy multiple editions of SQL Server including Express, Web, Standard and Enterprise, in minutes with cost-efficient and resizable compute capacity.

  • Amazon RDS for SQL Server DB Instances can be provisioned with either standard storage or Provisioned IOPS storage. Amazon RDS Provisioned IOPS is a storage option designed to deliver fast, predictable, and consistent I/O performance, and is optimized for I/O-intensive, transactional (OLTP) database workloads.
  • Using the Amazon RDS APIs or with a few clicks on the AWS Management Console, customers can provision the IOPS for your SQL Server DB Instance. They can create new DB Instances using the AWS Management Console or the Amazon RDS APIs, you can provision from 1,000 IOPS to 32,000 IOPS with corresponding storage from 100GB to 16TB for new SQL Server DB Instances.

MySQL

MySQL is the most widely adopted open source relational database and serves as the primary relational data store for many popular websites, applications, and commercial products. With more than 20 years of community-backed development and support, MySQL is a reliable, stable, and secure SQL-based database management system. The MySQL database is suitable for a wide variety of use cases, including mission critical apps, dynamic websites, and as an embedded database for software, hardware, and appliances.

AWS supports MySQL in a variety of ways, including a fully managed database service, Amazon Relational Database Service (RDS) for MySQL. Amazon Aurora with MySQL compatibility is also built using MySQL, and Amazon RDS supports the popular MySQL fork project, MariaDB. AWS customers can also host MySQL on Amazon EC2 and self-manage the database, or browse the 3rd party MySQL offerings on AWS Marketplace.

  • Amazon RDS provides two SSD-backed storage options for your MySQL database. General Purpose storage provides cost-effective storage for small or medium-sized workloads. For high-performance OLTP applications, Provisioned IOPS delivers consistent performance of up to 40,000 IOs per second. As your storage requirements grow you can provision additional storage on-the-fly with zero downtime.
  • The automated backup feature of Amazon RDS enables recovery of your MySQL database instance to any point in time within your specified retention period of up to thirty five days. In addition, you can perform user-initiated backups of your DB Instance. These full database backups will be stored by Amazon RDS until you explicitly delete them.
  • As a managed service, Amazon RDS provides a high level of security for your MySQL databases. These include network isolation using Amazon Virtual Private Cloud (VPC), encryption at rest using keys you create and control through AWS Key Management Service (KMS) and encryption of data in transit using SSL.
  • Amazon RDS Multi-AZ deployments provide enhanced availability and durability for your MySQL databases, making them a natural fit for production database workloads. Amazon RDS Read Replicas make it easy to elastically scale out beyond the capacity constraints of a single database instance for read-heavy database workloads.

PostgreSQL

PostgreSQL is an advanced, enterprise class open source relational database that supports both SQL (relational) and JSON (non-relational) querying. It is a highly stable database management system, backed by more than 20 years of community development which has contributed to its high levels of resilience, integrity, and correctness. PostgreSQL is used as the primary data store or data warehouse for many web, mobile, geospatial, and analytics applications.

With Amazon RDS, AWS clients can deploy scalable PostgreSQL deployments in minutes with cost-efficient and resizable hardware capacity. Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades; storage management; replication for high availability and read throughput; and backups for disaster recovery. Amazon RDS for PostgreSQL gives customers access to the capabilities of the familiar PostgreSQL database engine. 

  • PostgreSQL possesses Multi-Version Concurrency Control (MVCC), point in time recovery, granular access controls, tablespaces, asynchronous replication, nested transactions, online/hot backups, a refined query planner/optimizer, and write ahead logging.
  • PostgreSQL’s write ahead logging makes it a highly fault tolerant database. Its large base of open source contributors lends it a built-in community support network. PostgreSQL is ACID compliant, and has full support for foreign keys, joins, views, triggers, and stored procedures, in many different languages.
  • PostgreSQL source code is available under an open source license, granting customers the freedom to use, modify, and implement it as fit, at no charge. PostgreSQL carries no licensing cost, which eliminates the risk for over-deployment.

Amazon Aurora

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups.

Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones (AZs).

  • Amazon Aurora is  5X the throughput of standard MySQL and 3X the throughput of standard PostgreSQL. This performance is on par with commercial databases, at 1/10th the cost. AWS clients can easily scale their database deployment up and down from smaller to larger instance types as their needs change, or let Aurora Serverless handle scaling automatically for them. 
  • Amazon Aurora is designed to offer greater than 99.99% availability, replicating 6 copies of your data across 3 Availability Zones and backing up your data continuously to Amazon S3. It transparently recovers from physical storage failures; instance failover typically takes less than 30 seconds. 
  • Amazon Aurora provides multiple levels of security for your database. These include network isolation using Amazon VPC, encryption at rest using keys you create and control through AWS Key Management Service (KMS) and encryption of data in transit using SSL. On an encrypted Amazon Aurora instance, data in the underlying storage is encrypted, as are the automated backups, snapshots, and replicas in the same cluster. 
  • Amazon Aurora is fully managed by Amazon Relational Database Service (RDS). You no longer need to worry about database management tasks such as hardware provisioning, software patching, setup, configuration, or backups. Aurora automatically and continuously monitors and backs up your database to Amazon S3, enabling granular point-in-time recovery. You can monitor database performance using Amazon CloudWatch, Enhanced Monitoring, or Performance Insights, an easy-to-use tool that helps you quickly detect performance problems.