• Relational databases store data with a defined schema. These are commonly used for transactional and traditional applications
• Key-value databases are optimized to store and retrieve key-value pairs in large volumes and in milliseconds, without the performance overhead and scale limitations of relational databases
• Document databases are designed to store data as documents. Data is typically represented as a readable document
• In-memory databases are used for read-heavy and compute-intensive applications that require low-latency access to data
• Graph databases are used for applications that need to enable users to query and navigate relationships between highly connected datasets

Amazon Relational Database Service (Amazon RDS) is a web service that makes it easier to set up, operate, and scale relational databases in the cloud. With Amazon RDS, you can manage common database administration tasks like OS patching, database updates, and backups. Supported database engines include PostgreSQL, MySQL, MariaDB, Oracle, and Microsoft SQL Server.

Amazon Aurora is part of the managed database service Amazon RDS. Aurora is MySQL and PostgreSQL compatible. With Aurora, you can combine the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open-source databases.

Amazon DynamoDB is a fully managed key-value, non-relational database service that provides fast and predictable performance with seamless scalability. With DynamoDB, you can create database tables that store and retrieve data and serve any level of request traffic. You can scale up or scale down your tables’ throughput capacity without downtime or performance degradation.

Amazon DocumentDB (with MongoDB compatibility) is designed from the ground up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently.

Amazon ElastiCache offers fully managed Redis and Memcached in-memory data stores. You can build data-intensive apps or improve the performance of your existing apps by retrieving data from high throughput and low latency in-memory data stores.

Amazon Neptune is a fast, reliable, fully managed graph database service for applications that work with highly connected datasets. Neptune offers read replicas for highly availability. You can create point-in-time copies, configure continuous backup to Amazon Simple Storage Service (Amazon S3) with replication across Availability Zones.

Amazon Redshift is an enterprise-level, petabyte scale, fully managed data warehousing service. With Amazon Redshift, you can achieve efficient storage and optimum query performance through a combination of massively parallel processing, columnar data storage, and very efficient, targeted data compression encoding schemes.