Amazon DynamoDB

In a nonrelational database, user creates tables. A table is a place for storing and quering the data. Nonrelational databases are sometimes referred to as “NoSQL Databases”, because they use structures other than rows and columns to organize data. One type of structural approach for nonrelational databases is key-value pairs. With key-value pairs, data is organized into items (keys), and items have attributes (values). Attributes can be thought of as different features of the data. In a key-value database, client can add or remove attributes from items in the table at any time. Additionally, not every item in the table has to have the same attributes.

Amazon DynamoDB is a key-value database service. It delivers single-digit millisecond performance at any scale. DynamoDB is serverless, which means that client does not have to provision, patch, or manage servers. No need to install, maintain, or operate software. As the size of database shrinks or grows, DynamoDB automatically scales to adjust for changes in capacity while maintaining consistent performance. This makes it a suitable choice for use cases that require high performance while scaling.

Amazon Redshift

Amazon Redshift is a data warehousing service that can be used for big data analytics. It offers the ability to collect data from many sources and helps to understand relationships and trends across data.

AWS Database Migration Service (AWS DMS)

AWS DMS enables clients to migrate relational databases, nonrelational databases, and other types of data stores. With AWS DMS, client moves data between a source database and a target database. The source and target database can be of the same type or different types. During the migration, source database remains operational, reducing downtime for any applications that rely on the database. For example, suppose that client has a MySQL database that is stored on premises in an Amazon EC2 instance or in Amazon RDS. Consider the MySQL database to be a source database. Using AWS DMS, client can migrate data to a target database, such as Amazon Aurora database.

Other use cases for AWS DMS :

• Development and test database migrations : enabling developers to test applications against production data without affecting production users
• Database consolidation : combining several databases into a single database
• Continuous replication : sending ongoing copies of data to other target sources instead of doing a one-time migration