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What is Amazon RDS?

Amazon Relational Database Service (Amazon RDS) streamlines the creation, administration, and scaling of relational databases in the cloud. It presents a budget-friendly and flexible capacity option while handling time-consuming management activities such as hardware setup, database configuration, applying updates, and conducting backups. This enables you to focus on enhancing your applications, ensuring they deliver optimal performance, robust availability, security, and compatibility. Amazon RDS provides a variety of database instance types tailored for memory, performance, or I/O optimization and supports a range of six popular database engines, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server. Furthermore, the AWS Database Migration Service simplifies the process of moving or replicating your current databases to Amazon RDS, ensuring an easy and efficient transition. Ultimately, Amazon RDS equips organizations with powerful database solutions while alleviating the complexities associated with management tasks. By choosing this service, businesses can gain more agility and focus on innovation instead of maintenance.

What is Amazon EC2 Auto Scaling?

Amazon EC2 Auto Scaling promotes application availability by automatically managing the addition and removal of EC2 instances according to your defined scaling policies. With the help of dynamic or predictive scaling strategies, you can tailor the capacity of your EC2 instances to address both historical trends and immediate changes in demand. The fleet management features of Amazon EC2 Auto Scaling are specifically crafted to maintain the health and availability of your instance fleet effectively. In the context of efficient DevOps practices, automation is essential, and one significant hurdle is ensuring that fleets of Amazon EC2 instances can autonomously launch, configure software, and recover from any failures that may occur. Amazon EC2 Auto Scaling provides essential tools for automating every stage of the instance lifecycle. Additionally, integrating machine learning algorithms can enhance the ability to predict and optimize the required number of EC2 instances, allowing for better management of expected shifts in traffic. By utilizing these sophisticated capabilities, organizations can significantly boost their operational effectiveness and adaptability to fluctuating workload requirements. This proactive approach not only minimizes downtime but also maximizes resource utilization across their infrastructure.

Media

Media

Integrations Supported

Amazon EC2
Observe
Amazon Quantum Ledger Database (QLDB)
Amazon Redshift
Arctype
Canonical Juju
Dash ComplyOps
Data Virtuality
EverSQL
Foglight
Huawei Cloud Data Lake Governance Center
Immuta
Releem
Satori
Senzing
Stack Identity
TiDB Cloud
Umbrelly Cloud
VinaHost

Integrations Supported

Amazon EC2
Observe
Amazon Web Services (AWS)

API Availability

API Availability

Pricing Information

$0.01
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/rds/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/autoscaling/

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Mobile Access
Monitoring
Performance Analysis
Queries
Relational Interface
Virtualization

RDBMS

Backup
Data Migration
Monitoring
Storage Optimization

Relational Database

Not specified

SQL Databases

Not specified

Categories and Features

Auto Scaling

Not specified

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