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DynamoDB vs Amazon Aurora — The Ultimate Comparison Amazon Rekognition

Posted on October 26, 2022 by

Categories: AWS

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For developers, AWS offers a variety of cloud-based database solutions. Others are NoSQL, while others are Relational.

This article contrasts DynamoDB and Aurora, two well-known database systems that are serverless and entirely managed by AWS.

Aurora and DynamoDB Shared Attributes

If you choose DynamoDB or Aurora, completely managed databases, you can devote all your effort to utilizing the database rather than managing it. High scalability requirements are met by both databases, and the capacity may expand automatically as needed.

The main distinction between both is that Aurora is a relational database, and DynamoDB is a NoSQL database.

DynamoDB is the victor of significant data volumes since it supports petabytes of data and scales up and down without any noticeable lag. However, Aurora cluster volume can also expand up to 128 Terabytes, albeit doing so might take up to 15 minutes.

Speed and Efficiency

Let’s first contrast the query performance and database access latency in great detail.

DynamoDB

Database tables that can store data and handle any volume of on-demand traffic may be made with DynamoDB. Additionally, SSDs’ excellent IO performance offers faster reaction times and lower latency for storing and accessing data of any size.

The computing resources required for database operations are supported by this server instance. It maintains low latency (millisecond latency) behind this method regardless of the size of your table. DynamoDB’s speed is enhanced by maintaining a better table architecture, efficiently leveraging keys and indexes for queries, and reducing the strain on the database.

Up to 10 quadrillion requests per day and more than 20 million requests per second are processed by DynamoDB. By looking at these data, I believe you can easily visualize its scalability.

A relational database system compatible with MySQL and PostgreSQL is called Aurora by Amazon. It has a throughput rate of five times that of standard MySQL output and three times that of standard PostgreSQL output. AWS claims that this is made feasible by Aurora’s Storage service architecture.

Minimizing the latency while writing in the foreground is one of the fundamental design tenets of this storage service. The majority of storage processing is moved to the background with this approach. It increases throughput. As a result, turning it into a high-performing, cloud-native relational database in AWS.

Security At-Rest Encryption

Both DynamoDB and Aurora need encryption keys kept in AWS KMS (Key Management Service) to offer encryption at rest. To produce, store, and maintain their encryption keys, we may utilize AWS KMS.

However, there are three ways for Amazon DynamoDB customers to encrypt the table using AWS KMS.

  • By default, DynamoDB’s key is encrypted and free (AWS-owned key).
  • KMS will charge you and safeguard the keys kept in your account (AWS-managed key).
  • Users have total control over KMS keys using KMS Customer Management Keys (CMK), which costs money (Customer-managed key).
  • There are customer-managed keys and AWS-managed keys in Amazon Aurora. The CMK capability in the AWS KMS will be referred to as client-managed or customer master keys.

Strength and Accessibility

All of the data in DynamoDB is duplicated across several physical nodes. For each geographical location, Amazon has placed these physical nodes in many zones (also known as availability zones) to maintain high durability and availability even in the event of a severe calamity like a fire or prolonged power loss. Others will help to sustain the operations if one copy is down. Additionally, SSDs come with excellent availability and data durability built in.

Zones that are supported by Amazon Aurora. After finishing the primary instance, users can generate 15 read-only replicas using single-master replication. One of these read-only instances will serve as the primary instance if there is an issue with the primary model (failover). When necessary, this system will operate automatically.

Restore and Backup

DynamoDB offers PITR (Point-in-Time Backups) and an on-demand backup feature to return to any prior database state. Any quantity of data may be backed up with DynamoDB without affecting performance or availability. The user does not have to bother about backup schedules or background running activities, and the backup procedure is quick. With only one click and one API call, AWS provides backup recovery.

The Amazon Aurora backup procedure was developed without performance hiccups or database service interruptions, just like DynamoDB. Backups from Amazon are kept in an S3 bucket. Aurora will automatically assign a 30-minute backup by default if we don’t provide a backup window. We may also restore data by building a new Aurora DB cluster using the backup information for Aurora.