Database

Question 1

Which benefits can a company gain by deploying a relational database on Amazon RDS instead of Amazon EC2?

(Select TWO.)

1. Automated backups
2. Schema management
3. Indexing of tables
4. Software patching
5. Root access to OS

Answer 1

1. Automated backups
4. Software patching

Two of the benefits of using a managed Amazon RDS service instead of a self-managed database on EC2 are that you get automated backups and automatic software patching.

• Schema management is incorrect. This is not a feature of the managed service.
• Indexing of tables is incorrect. This is not a feature of the managed service.
• Root access to OS is incorrect. You do not get root access to an RDS instance’s operating system.

Reference:
What is Amazon Relational Database Service (Amazon RDS)?

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Question 2

A company is deploying a MySQL database on AWS. The database must easily scale and have automatic backup enabled.

Which AWS service should the company use?

1. Amazon Athena
2. Amazon DynamoDB
3. Amazon Aurora
4. Amazon DocumentDB

Answer 2

3. Amazon Aurora

Amazon Aurora is a relational database that is compatible with MySQL and PostgreSQL database engines. Aurora is extremely fast and scales up to 128 TB. You can also deploy replicas for read scaling within and across Regions. Aurora also offers automated backups.

• Amazon DynamoDB is incorrect. DynamoDB is a NoSQL (non-relational) database and you cannot deploy a MySQL database as it is a relational database type.
• Amazon Athena is incorrect. Athena is used for querying data in Amazon S3 using SQL.
• Amazon DocumentDB is incorrect. DocumentDB is a NoSQL database that supports document data structures.

Reference:
Amazon Aurora features

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Question 3

Which AWS-managed service can be used to process vast amounts of data using a hosted Hadoop framework?

1. Amazon DynamoDB
2. Amazon Athena
3. Amazon EMR
4. Amazon Redshift

Answer 3

3. Amazon EMR

Amazon Elastic Map Reduce (EMR) is a web service that enables businesses, researchers, data analysts, and developers to easily and cost-effectively process vast amounts of data. EMR utilizes a hosted Hadoop framework running on Amazon EC2 and Amazon S3.

• Amazon DynamoDB is incorrect. DynamoDB is not a hosted Hadoop framework, it is a no-SQL database.
• Amazon Athena is incorrect. Amazon Athena is a serverless, interactive query service to query data and analyze big data in Amazon S3 using standard SQL
• Amazon Redshift is incorrect. Amazon Redshift is a fast, simple, cost-effective data warehousing service.

Reference:
Amazon EMR

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Question 4

A company is interested in moving its on-premises NoSQL database into the AWS Cloud.

Which AWS service should the company use to replace their existing database?

1. Amazon Redshift
2. Amazon RDS for MySQL
3. Amazon Quantum Ledger Database (Amazon QLDB)
4. Amazon DynamoDB

Answer 4

4. Amazon DynamoDB

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB offers built-in security, continuous backups, automated multi-Region replication, in-memory caching, and data export tools. When you hear of AWS Managed NoSQL databases, DynamoDB is the only acceptable choice.

• Amazon RDS for MySQL is incorrect as RDS is a managed Relational (SQL) database service. The question calls for a NoSQL database.
• Amazon Quantum Ledger Database (Amazon QLDB) is incorrect. Amazon Quantum Ledger Database (QLDB) is a fully managed ledger database that provides transparent, immutable, and cryptographically verifiable transactions- and is not a suitable replacement for an on-premises NoSQL database.
• Amazon Redshift is incorrect, as it is an SQL-based data warehousing solution. It would not be a suitable replacement for an on-premises NoSQL database.

Reference:
Amazon DynamoDB

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Question 5

What is a benefit of moving an on-premises database to Amazon Relational Database Service (RDS)?

1. There is no need to manage operating systems
2. You can scale vertically without downtime
3. There is no database administration required
4. You can run any database engine

Answer 5

1. There is no need to manage operating systems

With Amazon RDS, which is a managed service, you do not need to manage operating systems. This reduces operational costs.

• You can scale vertically without downtime is incorrect. You cannot scale vertically without downtime. When scaling with RDS you must change the instance type, and this requires a short period of downtime while the instances’ operating system reboots.
• There is no database administration required is incorrect. There is still database administration required in the cloud. You don’t manage the underlying operating system but still need to manage your own tables and data within the DB.
• You can run any database engine is incorrect. You cannot run any database engine with RDS. The options are MySQL, Microsoft SQL, MariaDB, Oracle, PostgreSQL and Aurora.

Reference:
Amazon RDS features

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Question 6

An IT company has deployed its infrastructure on the AWS cloud. There must be a database that supports reads with a latency of under a millisecond for critical applications.

Which AWS service will meet this requirement?

1. Amazon EMR
2. Amazon RDS
3. AWS Glue
4. Amazon ElastiCache

Answer 6

4. Amazon ElastiCache

Amazon ElastiCache s is a blazing fast in-memory data store that provides sub-millisecond latency to power internet-scale real-time applications. Built on open-source Redis or Memcached, ElastiCache works seamlessly with Redis or Memcached without any code changes.

• Amazon EMR is incorrect, as Amazon EMR is a cloud big data platform that can be queried using SQL. This is not a database solution designed to be used for single millisecond latency.
• AWS Glue is incorrect. AWS Glue is an event-driven, serverless computing platform. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code. This does not store data natively and cannot handle rapid queries.
  Amazon RDS is incorrect. Whilst RDS is a database solution, it cannot handle single millisecond queries.

Reference:
Amazon ElastiCache

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Question 7

Which AWS service supports an in-memory data structure store, compatible with Redis, that delivers sub-millisecond latency for use cases such as caching, session stores, and real-time analytics?

1. Amazon DynamoDB
2. Amazon RDS
3. Amazon MemoryDB
4. Amazon Redshift

Answer 7

3. Amazon MemoryDB

Amazon MemoryDB for Redis is the correct answer because it is a Redis-compatible, in-memory database service built on Redis architecture, which offers sub-millisecond latency, fulfilling the requirements mentioned in the question.

• Amazon DynamoDB is incorrect because, while it is a key-value and document database that delivers single-digit millisecond performance at any scale, it is not a Redis-compatible in-memory data structure store designed specifically to offer sub-millisecond latency for the use cases mentioned.
• Amazon RDS is incorrect because, although it is a relational database service that supports several database engines, it does not inherently support an in-memory data structure store that is compatible with Redis for sub-millisecond latency performance.
• Amazon Redshift is incorrect because it is a data warehousing solution optimized for analytic queries against large datasets and is not designed as a Redis-compatible in-memory data structure store offering sub-millisecond latency.

Reference:
Amazon MemoryDB

Question 8

In order to perform analytical tasks, a company needs a data warehouse. Standard SQL queries must be supported by the data warehouse.

Which AWS service meets these requirements?

1. Amazon EMR
2. Amazon Athena
3. Amazon Redshift
4. Amazon RDS

Answer 8

3. Amazon Redshift

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning to deliver the best price performance at any scale.

Data warehouses are built on databases designed for online analytics processing (OLAP) use cases.

• Amazon Athena is incorrect. Amazon Athena is a serverless query service which you can use to query S3 using standard SQL.
• Amazon EMR is incorrect. Amazon EMR is a cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and machine learning (ML) applications using open-source analytics frameworks such as Apache Spark, Apache Hive, and Presto.
• Amazon RDS is incorrect. RDS is typically used as an online transaction processing (OLTP) database rather than an OLAP database.

Reference:
Amazon Redshift

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Question 9

An organization is migrating its application from on-premises SQL Server to AWS. As part of the migration, the company wants to reduce operational overhead, but lacks the resources to refactor the application.

Which database service would MOST effectively support these requirements?

1. Amazon DynamoDB
2. Amazon Redshift
3. Microsoft SQL Server on Amazon EC2
4. Amazon RDS for SQL Server

Answer 9

4. Amazon RDS for SQL Server

Amazon RDS for SQL Server is a fully managed SQL database service which you can migrate your on-premises database into. You do not need to refactor or change your on-premises database and you can perform homogeneous migrations with ease.

• Amazon Redshift is incorrect. RedShift is a data warehousing solution which would not accept a migration using SQL Server.
• Microsoft SQL Server on Amazon EC2 is incorrect. Although you can launch a SQL server on EC2, this question states that the company wants to reduce operational overhead and managing SQL Server on EC2 would include more operational overhead compared to using RDS for SQL Server.
• Amazon DynamoDB is incorrect. DynamoDB is a No-SQL database that is not suitable for a direct 1-1 migration from an SQL database without schema conversion.

Reference:
Amazon Relational Database Service

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Question 10

Which type of Amazon RDS automated backup allows you to restore the database with a granularity of as little as 5 minutes?

1. Snapshot backup
2. Full backup
3. Incremental backup
4. Point-in-time recovery

Answer 10

4. Point-in-time recovery

You can restore an Amazon RDS database instance to a specific point in time with a granularity of 5 minutes. Amazon RDS uses transaction logs which it uploads to Amazon S3 to do this.

• Snapshot backup is incorrect. This is not a point-in-time backup with 5 minute granularity.
• Full backup is incorrect. This just describes taking a fully backup of the database, typically with backup software.
• Incremental backup is incorrect. This describes taking a backup of items that have changed since the last backup.

Reference:
Restoring a DB instance to a specified time for Amazon RDS

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Question 11

Which DynamoDB feature provides in-memory acceleration to tables that result in significant performance improvements?

1. Amazon ElastiCache
2. Amazon DynamoDB Accelerator (DAX)
3. Amazon EFS
4. Amazon CloudFront

Answer 11

2. Amazon DynamoDB Accelerator (DAX)

Amazon DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from milliseconds to microseconds – even at millions of requests per second.

DAX does all the heavy lifting required to add in-memory acceleration to your DynamoDB tables, without requiring developers to manage cache invalidation, data population, or cluster management.

• Amazon ElastiCache is incorrect. This service is also an in-memory cache but it is not a feature of DynamoDB.
• Amazon EFS is incorrect. This is an elastic filesystem based on the NFS protocol.
• Amazon CloudFront is incorrect. This is a content delivery network for caching content.

Reference:
Amazon DynamoDB Accelerator (DAX)

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