Specialization in Amazon Aurora
Amazon Aurora is a relational database compatible with MySQL and PostgreSQL, built on AWS Cloud to deliver up to five times the speed of standard MySQL databases and three times the speed of standard PostgreSQL databases!
Amazon Aurora automatically manages data storage according to your application's needs, creating 6 copies of data in 3 availability zones, ensuring high availability and read replicas with latencies in the milliseconds range.
Aurora is part of Amazon Relational Database Service (Amazon RDS) and leverages RDS resources for database management and administration. You can increase data read capacity and performance by adding up to 15 read replicas across three availability zones with the click of a button.
Benefits of Amazon Aurora
CloudDog is an AWS Partner with various specialties. One of them is Database Migration to AWS, where we use Amazon Aurora as a managed database service to ensure the best performance, security, and data availability for your company.
Discover Our Differences
The main benefits of AWS Config are:
Planning: CloudDog has extensive experience in database migration to AWS, supporting all planning needs for a successful migration project.
Proof of Concept: Working closely with Amazon Web Services, we conduct Proof of Concept projects with clients to validate application compatibility with Amazon Aurora databases, providing decision-making with high accuracy.
Load Testing: We assess critical application operations with clients to ensure a smooth migration process without surprises.
Migration from Oracle Database: We perform Oracle database migrations to Amazon Aurora PostgreSQL using the Database Migration Service.
Amazon Aurora Differences
During migration projects, CloudDog identified some use cases that are possible with Amazon Aurora:
Increase Your Database Availability
RDS MySQL offers Multi-AZ configuration as a fault-tolerance strategy and allows adding read replicas. However, the Multi-AZ instance is not usable, and replication time between the source and replicas is often high, inhibiting its effectiveness in some scenarios.
With Amazon Aurora, when you create a Cluster, a high-performance, highly available managed storage service is created, shared among all read replicas, enabling synchronization with very low latency.
In the event of an original instance failure, a replica will be automatically promoted to a new original instance, restoring processing in a short time.
Distribute Your Multi-Tenant Application's Load
SaaS applications often use Multi-Tenant databases, where a single database serves multiple clients, making database scalability complex but essential when service usage increases.
With Amazon Aurora, you can configure a Cluster with multiple Write/Read instances, increasing application availability and computing power.
In case of an instance failure, any other instance can continue processing.
SaaS applications configured to use Amazon Aurora Multi-Master can employ custom load balancing strategies, prioritizing client traffic to specific instances.
Accelerate Analytical Reporting
Amazon Aurora executes analytical queries using the Parallel Query option, allowing queries to be run directly on the Cluster Storage, reducing execution time.
It also improves the execution of transactional operations and analytical queries.
Reduce Database Change Risks (Fast DB Clone)
Test structural changes or database cleanups using a clone of the production database.
With fast database cloning, you can create databases sharing the same data as the original database.
When testing the cloned database, only blocks related to changed data will occupy new storage space.
Quickly Recover to a Previous State
Occasionally, despite taking all precautions, the worst can happen, such as the deletion of an important table or unintentional data changes during maintenance.
With the Backtracking feature, you can return the database to a previous state and recover deleted data.
In the scenario below, the ITEM table is deleted at 10:30:15, and the database returns to the previous state at 10:35:20.
The backtracking option must be configured to enable its use.
Dynamically Scale Capacity to Meet Demand
In a traditional database, capacity is often provisioned to handle peak usage, leading to idle times and waste.
With Amazon Aurora, you can configure smaller instances, allowing for increased fault tolerance strategies.
When the number of users increases, in the previous scenario, users may already experience performance loss, while Amazon Aurora can add extra capacity to handle the demand.
In the previous scenario, if the number of users continues to increase, users start to experience widespread application processing failures, potentially resulting in revenue loss. Amazon Aurora continues to scale to accommodate additional demand.
AWS Partner and AWS Certified Partner
CloudDog's journey began in 2019 when the company achieved the AWS Select Partner tier. Since then, it has maintained a total focus on the Amazon Web Services ecosystem. Over the following years, the team earned several key certifications, standing out in 2020 by becoming the second partner in Brazil to be validated for Amazon CloudFront.
The major milestone of this evolution came in 2023, when the company upgraded to AWS Advanced Partner Tier, a direct result of its technical expertise and the successful delivery of over 100 cloud projects.
Today, CloudDog has reached a new level of technical maturity. The company now holds four AWS Competencies (SMB, Cloud Operations, AI Services, and DevOps Consulting) and 14 Service Validations (SDPs), covering essential tools like Control Tower, EKS, Lambda, and databases. To further strengthen its end-to-end capabilities, CloudDog joined the Well-Architected program and earned the rigorous AWS Managed Service Provider (MSP) validation, proving its excellence in the continuous management and support of cloud environments.
Currently, CloudDog is fully prepared to support companies through every stage of their technological journey. Backed by a team holding all AWS certifications, the company handles everything from workload migrations to daily environment support and optimization. These achievements serve as practical proof of CloudDog's position as a trusted consultancy, focused on delivering solid, secure, and high-quality results.
Frequently Asked Questions
How is data encryption done in Amazon Aurora?
Amazon Aurora allows you to encrypt your databases using keys you manage through the AWS Key Management Service. In a database instance running with Amazon Aurora encryption, the data stored at rest in the underlying storage is encrypted, as well as your automated backups, snapshots, and replicas in the same cluster.
What is the difference between Amazon RDS and Amazon Aurora?
With Amazon Aurora, you can provision up to 15 replicas, and synchronization occurs in milliseconds. On the other hand, RDS allows only five replicas, and the replication process is slower than Amazon Aurora. Replicas in Amazon Aurora share Cluster Storage.
Is Amazon Aurora faster than RDS MySQL Community?
Yes, Amazon Aurora comes with several optimizations enabled by Cluster Storage, allowing it to handle up to 5x more operations than RDS MySQL Community using the same instance type.
How many instances can Amazon Aurora have in a Multi-Master configuration?
Currently, Amazon Aurora supports 2 instances in the Multi-Master configuration, although this limitation may be removed at any time.
Is Amazon Aurora compatible with MySQL?
Yes, most of the code, applications, drivers, and tools you already use with MySQL databases can be used with Amazon Aurora with little or no modification. The Amazon Aurora database engine is designed to be wire-compatible with MySQL 5.6 and 5.7 using the InnoDB storage engine.
How to migrate from the Oracle Database to Amazon Aurora?
To migrate from an Oracle database to Amazon Aurora, you need to configure database schema mapping, replicate data between the Oracle database and the Aurora PostgreSQL database using the Database Migration Service. Then, you should review the optimization of table indexes and other artifacts.
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