20 Amazon Aurora Interview Questions and Answers

Amazon Aurora is a cloud-based relational database service that offers high performance, availability, and security. As a potential Amazon Aurora user, you may be asked questions about its features and capabilities during a job interview. Answering these questions confidently can help you demonstrate your knowledge and earn the position you desire. In this article, we review some of the most commonly asked Amazon Aurora questions and provide tips on how to answer them.

Amazon Aurora Interview Questions and Answers

Here are 20 commonly asked Amazon Aurora interview questions and answers to prepare you for your interview:

1. What is Amazon Aurora?

Amazon Aurora is a relational database service that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It is designed to be compatible with MySQL and PostgreSQL, and offers up to five times better performance than MySQL.

2. Can you explain what a DB cluster is in the context of Amazon Aurora?

A DB cluster is a collection of Amazon Aurora DB instances that share a common database and can be used to scale read and write capacity.

3. How do you create an Amazon Aurora DB instance?

You can create an Amazon Aurora DB instance using the Amazon RDS console, the AWS Command Line Interface, or the Amazon RDS API.

4. Can you give me some examples of how to connect to Amazon Aurora using common programming languages?

You can connect to Amazon Aurora using common programming languages like Java, Python, Node.js, and PHP. For example, in Java you would use the Amazon Aurora JDBC driver. In Python you would use the mysql.connector module. In Node.js you would use the mysql module. And in PHP you would use the mysqli or PDO extension.

5. Is it possible to use AWS Lambda functions with Amazon Aurora? If yes, then how?

Yes, it is possible to use AWS Lambda functions with Amazon Aurora. You can do this by creating a Lambda function that uses the Aurora Data API to insert, update, or delete data in an Amazon Aurora database.

6. How can you scale your Amazon Aurora database?

There are a few ways to scale your Amazon Aurora database. One way is to increase the number of Aurora Replicas. This will allow you to increase read performance and availability. Another way to scale is to increase the size of your database instance. This will allow you to increase the amount of storage and compute power available to your database.

7. Can you explain what PostgreSQL compatibility means in the context of Amazon Aurora?

Amazon Aurora is a relational database engine that is compatible with PostgreSQL. This means that it can natively read and write PostgreSQL database files, and it can also connect to existing PostgreSQL databases to query and update data.

8. What are the advantages and disadvantages of using Amazon Aurora over MySQL or PostgreSQL?

The main advantage of Amazon Aurora over MySQL or PostgreSQL is that it is designed to be compatible with MySQL and PostgreSQL, while also offering improved performance and scalability. The main disadvantage is that it is a proprietary database engine, so it is not as widely adopted as MySQL or PostgreSQL.

9. What do you understand about the difference between EBS-backed and Instance Store-backed storage for Amazon Aurora instances?

EBS-backed storage is used for the storage of data that is persistent and will not be lost if the instance is stopped or terminated. Instance Store-backed storage is used for data that is not persistent and will be lost if the instance is stopped or terminated.

10. What is the default retention period for data stored in an Amazon Aurora database snapshot?

The default retention period for data stored in an Amazon Aurora database snapshot is 30 days.

11. What is the maximum number of concurrent connections allowed for an Amazon Aurora instance?

The maximum number of concurrent connections allowed for an Amazon Aurora instance is 1,000.

12. What does the max_connections parameter define in the context of Amazon Aurora?

The max_connections parameter defines the maximum number of concurrent connections that Amazon Aurora will allow. This parameter can be used to help control costs and manage performance.

13. Are there any limitations on the size of tables that can be created in Amazon Aurora?

There are no size limitations on Amazon Aurora tables. You can create tables that are as large as you need them to be to accommodate your data.

14. What happens if I delete an Amazon Aurora DB Cluster without taking a backup?

If you delete an Amazon Aurora DB Cluster without taking a backup, then all of your data will be permanently lost. There is no way to recover it.

15. What’s the best way to stream realtime updates from Amazon Aurora into Apache Spark clusters?

One way to stream realtime updates from Amazon Aurora into Apache Spark clusters is to use the Amazon Kinesis Data Streams service. This service can be used to collect and process streaming data in real time. It can also be used to connect to other services, such as Amazon Aurora, in order to process and analyze data.

16. What do you understand about the concept of high availability in Amazon Aurora?

High availability in Amazon Aurora refers to the ability of the system to remain operational and accessible even in the event of a failure or outage. This is achieved through a combination of features such as self-healing storage, multi-AZ deployments, and read replicas.

17. What are read replicas? Why are they used?

Read replicas are used in Amazon Aurora to provide a way to scale out reads for an Aurora DB cluster. By creating a read replica, you can offload read traffic from the primary DB instance to the read replica. This can improve the performance of your Aurora DB cluster overall.

18. Why should we consider using Amazon Aurora instead of Amazon RDS?

Amazon Aurora is a relational database service that is fully compatible with MySQL and PostgreSQL. Aurora is designed to be more scalable and performant than RDS, and is up to five times faster than MySQL and three times faster than PostgreSQL. In addition, Aurora offers features like automatic failover and point-in-time recovery that are not available in RDS.

19. What are the different types of engine modes supported by Amazon Aurora?

There are two types of engine modes supported by Amazon Aurora: serverless and provisioned. Serverless is the more cost-effective option, as it only charges for the resources used while the database is active. Provisioned is more expensive but offers more control over database performance.

20. What are the minimum requirements needed to run Amazon Aurora?

Amazon Aurora requires a minimum of two Amazon Aurora DB instances in order to function properly. Each DB instance must have a minimum of 1 GB of storage and a maximum of 64 GB of storage. In addition, each DB instance must have a minimum of 500 MB/s of dedicated bandwidth and a maximum of 10 Gbps of dedicated bandwidth.