The modernization process – part1 (AWS databases)
Today is the generation of modernization in every field and IT is the flag bearer of this. Every firm who wants to see themselves in an extensive manner willing to induce in modernization by moving towards the cloud irrespective of their ways; either it is private, public or hybrid.
The main issue arises when the firm wants to move their huge stacks of data to the cloud. It seems like it will take days and days to perform the task and it will cost them a fortune. So, what firms really want? the answer is:
minimal disruption to their clients.
⦁ accuracy of data
⦁ optimum resource utilization.
⦁ less time consumption
⦁ and above all, cost optimization
So for all these criteria given, AWS has their back! AWS provides a number of solutions to their clients concerning the issues of migrating their data to the cloud, keeping their needs on priorities.
Let’s start with relational databases, so a Relational database or SQL database is a structured way of storing data in the form of tables consisting of columns and rows. In AWS you have Amazon Aurora, Amazon RDS and Amazon redshift.
We’ll initiate discussion with amazon aurora, it is compatible with MySQL and PostgreSQL databases that combines the performance and availability of your enterprise databases with cost-optimization. It is up to three times faster than PostgreSQL and five times faster than MySQL databases.
Aurora is a self-healing and fault-tolerant storage system that automatically scales up to 128TB per database instance. You can easily scale up and down your database deployment from smaller to larger instance type with respect to your requirements. Across 3 Availability Zones you can add up to 15 low latency read replicas to scale read capacity and performance.
Aurora offers 99.99% availability by replicating copies of your data across 3 availability zones which makes it durable. Aurora can span multiple AWS regions to enable fast local reads and it works great in case of disasters as well with a highly disaster recovery attribute. Cross-region Aurora replicas use either physical or logical replication. Aurora Global Database called Physical Replication, uses dedicated infrastructure that leaves your databases completely available to serve your applications, and can replicate to up to 5 secondary regions with typical latency of under a second. It’s available for both Aurora PostgreSQL and Aurora MySQL. For low-latency global reads and disaster recovery, it is recommended to use Aurora Global Database.
You can secure your data with an extra security layer of KMS (AWS key management Service) when the data is at rest and the SSL encrypts your data while transitioning. On an encrypted Amazon Aurora instance, data in the underlying storage is encrypted, as automated backups, snapshots, and replicas in the same cluster.
For migration from MySQL to Aurora, you have several options. You can use MySQL import utility to import data to Amazon Aurora and standard MySQL dump utility to export data from MySQL, and vice-versa. By AWS Management Console you can use Amazon RDS’s DB Snapshot migration feature to migrate an RDS MySQL DB snapshot to Amazon Aurora. Mostly migration completes for customers under an hour, though’ the period depends on data set size and format.
This goes for PostgreSQL DB as well.
Stay connected for more information on AWS. For now, here are some of the databases AWS offer and you can select from it as per your requirement.


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