Amazon Aurora Insights from Minjar
Minjar is a Premier Consulting Partner of AWS and offers a comprehensive portfolios of offerings including Managed Cloud, Cloud Migration and our advisory offering – Smart Assist. Database solutions form an integral part of our offerings and we are engaged with our customers through Architecture advisory, technical design, implementation and migration and ongoing managed services / optimization of database environments. As part of these activities, Minjar looks are performance and cost optimization opportunities and we have seen customer use cases where existing MySQL databases can be upgraded to Aurora for higher price performance. Minjar Cloud practice team is constantly evaluating opportunities to optimize client databases to leverage Aurora where its applicable. In this post we share some of our learnings and best practices on Amazon Aurora.
Amazon Aurora is a relational database engine from Amazon Web Services. Aurora engine is compatible with MySQL, which means applications and drivers used in databases relying on MySQL can be used in Aurora with almost no changes.
Amazon Relational Database Service (RDS) manages Aurora databases by handling provisioning, patching, backup, recovery and other tasks. Aurora stores a minimum of 10 GB and automatically scales to a maximum of 64 TB size. The service divides the volume of a database into 10 GB chunks, which are spread across different disks. Each chunk is replicated six ways across three AWS Availability Zones (AZs). If data in one AZ fails, Aurora attempts to recover data from another AZ. Aurora is also self-healing, meaning it performs automatic error scans of data blocks and disks.
Developers can scale up resources allocated to a database instance and improve availability through Amazon Aurora Replicas, which share the same storage as the Elastic Compute Cloud (EC2) instance. An Amazon Aurora Replica can be promoted to a primary instance without any data loss, which helps with fault tolerance if the primary instance fails. If a developer has made an Aurora Replica, the service automatically fails over within one minute; it takes about 15 minutes to fail over without a replica.
AWS Aurora was built to deliver significantly improved parallel processing and concurrent I/O operations. In traditional database engine architectures (like Mysql, MSSQL, and Oracle), all layers of data functionality – like SQL, transactions, caching, and logging – reside in single box.
But when you provision Amazon Aurora, logging and caching are moved into a “multi tenant, scale-out database-optimised storage service” that’s deeply integrated with other AWS compute and storage services. Besides allowing you to dramatically scale without nearly the overhead, you can restart the database engine without losing the cache.
Some key reasons where we recommend AWS Aurora in comparison to MySQL are:
5x increase in performance when compared to MySQL.
Designed to detect database crashes and restart without the need for manual crash recovery
SSL (AES-256) encryption to secure data in transit
You can provision upto15 read replica.
Migration approach
You can easily migrate from RDS MySQL to Aurora. You can provision Aurora instance from any of the existing RDS MySQL snapshot.
AWS Aurora is fully compatible AWS Database Migration Service (DMS). You can migrate or convert any of the existing database to Aurora using DMS service. If you need to convert the database engine then first you need to use AWS Schema Conversion tool.

















