Amazon ElastiCache is an in-memory database. With ElastiCache Memcached there is no data
replication or high availability, while the Redis engine must be used which does support both data replication and
clustering.

Memcached does not support data replication or high availability.

• MySQL is the world's most popular open source relational database and Amazon RDS makes it easy to set up, operate, and scale MySQL deployments in the cloud. With Amazon RDS, you can deploy scalable MySQL servers in minutes with cost-efficient and resizable hardware capacity.
• Amazon RDS for MySQL frees you up to focus on application development by managing time-consuming database administration tasks including backups, software patching, monitoring, scaling and replication.

Amazon RDS makes it easy to set up, operate, and scale PostgreSQL deployments in the cloud. With Amazon RDS, you can deploy scalable PostgreSQL deployments in minutes with cost-efficient and resizable hardware capacity. Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades; storage management; replication for high availability and read throughput; and backups for disaster recovery.

1. "in-memory database" - indicate towards Amazon ElastiCache, so last two options are removed.
2. that supports data replication - Only Amazon ElastiCache for Redis  supports data replication.

Amazon Simple Notification Service (SNS) is used for sending notifications using topics. Amazon SQS is a better solution for this scenario as it provides a decoupling mechanism where the actual images can be stored for processing. SNS does not provide anything for the images to be stored.

We use Amazon SQS to decouple the front end from the processing compute layer. To do this we can create a custom CloudWatch metric that measures the number of messages in the queue and then configure the ASG to scale using a target tracking policy that tracks a certain value.

• Target tracking scaling policy adds or removes capacity as required to keep the metric at, or close to, the specified target value. In addition to keeping the metric close to the target value, a target tracking scaling policy also adjusts to changes in the metric due to a changing load pattern.
• However, Using a target tracking policy with the ASG that tracks CPU utilization does not allow scaling based on the number of images being uploaded.

• Scheduled scaling helps you to set up your own scaling schedule according to predictable load changes.
• Example: - Let's say that every week the traffic to your web application starts to increase on Wednesday, remains high on Thursday, and starts to decrease on Friday. You can configure a schedule for Amazon EC2 Auto Scaling to increase capacity on Wednesday and decrease capacity on Friday.
• Using a scheduled policy is less useful as though you may be able to predict usage patterns, it would be better to adjust dynamically based on actual usage.

1. Decoupled - indicates towards SQS as it is best solution to decouple the front end from the processing compute layer.

BEWARE:-

1. ASG needs to dynamically adjust based on the number of images being uploaded - Indicates towards target tracking policies, which might divert you towards option C , but the earlier requirment of decoupling is not taken care in oprion C, so option C is not correct.

• Used to Analyze all of your data with the cloud data warehouse.
• Fastest and most widely used cloud data warehouse.
• Amazon RedShift is a data warehouse service used for online analytics processing (OLAP) workloads

• Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.
• It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups.
• It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need.
• Amazon RDS is a relational (SQL) type of database, not a key-value / nonrelational database.

• A key-value database is a type of nonrelational (NoSQL) database that uses a simple key-value method to store data.
• A key-value database stores data as a collection of key-value pairs in which a key serves as a unique identifier.
• Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability
• Fast and flexible NoSQL database service for any scale

• Amazon ElastiCache allows you to seamlessly set up, run, and scale popular open-source compatible in-memory data stores in the cloud.
• Build data-intensive apps or boost the performance of your existing databases by retrieving data from high throughput and low latency in-memory data stores.
• Amazon ElastiCache is a popular choice for real-time use cases like Caching, Session Stores, Gaming, Geospatial Services, Real-Time Analytics, and Queuing.
• Amazon ElastiCache is an in-memory caching database. This is not a nonrelational key-value database.

"key-value database" - Out of all four options only DynamoDB is key-value database.

• Amazon RedShift - Data warehouse service
• Amazon RDS - Relational (SQL) type of database, while key-value is non-relational database.
• Amazon ElastiCache - In-memory caching database