As the cloud continues to drive down the cost of storage and compute, a new generation of applications have emerged, creating a new set of requirements for databases. These applications need databases to store terabytes to petabytes of new types of data, provide access to the data with millisecond latency, process millions of requests per second, and scale to support millions of users anywhere in the world. To support these requirements, you need both relational and non-relational databases that are purpose-built to handle the specific needs of your applications. AWS offers the broadest range of databases purpose-built for your specific application use cases. 

AWS Purpose-built Databases
AWS Databases

Our fully managed database services include relational databases for transactional applications, non-relational databases for internet-scale applications, a data warehouse for analytics, an in-memory data store for caching and real-time workloads, and a graph database for building applications with highly connected data. If you are looking to migrate your existing databases to AWS, the AWS Database Migration Service makes it easy and cost effective to do so. 

If You Need Consider Using Product Type
A fully managed MySQL and PostgreSQL-compatible relational database with the performance and availability of enterprise databases at 1/10th  the cost. Amazon Aurora Relational Database
A managed relational database in the cloud that you can launch in minutes with just a few clicks. Amazon RDS Relational Database
A serverless, NoSQL database that delivers consistent single-digit millisecond latency at any scale. Amazon DynamoDB NoSQL Database
A fast, fully managed, petabyte-scale data warehouse at 1/10th the cost of traditional solutions. Amazon Redshift Data Warehouse
To deploy, operate, and scale an in-memory data store based on Memcached or Redis in the cloud. Amazon ElastiCache In-Memory Data Store
A fast, reliable, fully managed graph database to store and manage highly connected data sets. Amazon Neptune Graph Database
Help migrating your databases to AWS easily and inexpensively with minimal downtime. AWS Database Migration Service Database Migration 
Consider Using
Transactional applications like ERP, CRM, and eCommerce to log transactions and store structured data. Amazon Aurora,
Amazon RDS
Internet scale applications like hospitality, dating, and ride sharing to serve content and store structured and unstructured data. Amazon DynamoDB
Analytic applications for operational reporting and querying Terabyte to Exabyte scale data. Amazon Redshift
Real-time application use cases that require sub-millisecond latency like gaming leaderboards, chat/messaging, streaming, and IoT. Amazon ElastiCache
Applications with use cases that require navigation of highly connected data like social news feeds, recommendations, and fraud detection. Amazon Neptune

Read Werner Vogels' blog on why developers are choosing purpose-built databases for well-architected applications.

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL and up to three times better performance than PostgreSQL with the security, availability, and reliability of a commercial database at one-tenth the cost. New for Aurora, is Aurora serverless, that simplifies administration, reduces costs, and delivers capacity on demand by automatically scaling up or scaling down without manual provisioning. Aurora also features multi-master to scale out both reads and writes by creating multiple read and write master nodes across availability zones for better performance and zero downtime. Both of these features are available in preview.

For more information visit the Amazon Aurora product page.

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 managing time-consuming database administration tasks, freeing you up to focus on your applications and business. Amazon RDS provides you six familiar database engines to choose from, including Amazon Aurora, Oracle, Microsoft SQL Server, PostgreSQL, MySQL and MariaDB.

For more information visit the Amazon RDS product page.  

Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document and key-value store models. Its flexible data model and reliable performance make it a great fit for mobile, web, gaming, ad tech, IoT, and many other applications. New for DynamoDB is global tables, which fully automate the replication of tables across AWS regions for a fully managed, multi-master, multi-region database. DynamoDB also adds support for on-demand and continuous backups for native data protection.

For more information visit the Amazon DynamoDB product page.

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all your data using your existing business intelligence tools. You can start small for $0.25 per hour with no commitments and scale to petabytes for $1,000 per terabyte per year, less than a tenth the cost of traditional solutions.

For more information visit the Amazon Redshift product page.

Amazon ElastiCache makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache for Redis offers fully managed Redis and ElastiCache for Memcached offers fully managed Memcached in the cloud.

For more information visit the Amazon ElastiCache product page.

Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Apache TinkerPop and W3C's RDF, and their associated query languages TinkerPop Gremlin and RDF SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security.

For more information visit the Amazon Neptune product page.

AWS Database Migration Services (DMS) helps you migrate databases to AWS easily and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database. The AWS Database Migration Service can migrate your data to and from most widely used commercial and open-source databases. The service supports homogenous migrations such as Oracle to RDS for Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to Amazon Aurora or Microsoft SQL Server to RDS for MySQL.

For more information visit the AWS DMS product page.

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Airbnb is using DynamoDB to store user search history due to the data volume and need for quick lookups to enable personalized search, ElastiCache to store session state in-memory for faster (sub-millisecond) site rendering, and RDS MySQL as their primary transactional database.



Capital One uses RDS to store transaction data for state management, Redshift to store web logs for analytics that need aggregations, and DynamoDB to store user data to provide quick access to customers via their mobile app.



Expedia built a real-time data warehouse for lodging market pricing and availability data for internal market analysis using Aurora, Redshift, and ElastiCache. The system processes high-volume lodging pricing and availability data, performing a multi-stream union and self-join with a 24-hour lookback window using ElastiCache for Redis, and persists the processed data directly into MySQL Aurora and Redshift to support both operational and analytical queries.



Johnson and Johnson is using AWS Database services such as RDS, DynamoDB, and Redshift to minimize time and efforts spend on gathering and provisioning data and quickly deriving insights. AWS database services are helping Johnson and Johnson improve physician compliance, optimize supply chain, and discover new drugs.



Zynga migrated the Zynga poker database from MySQL farm to DynamoDB and got a massive performance boost, with queries that used to take 30 seconds now taking one second. Amazon ElastiCache (Memcached and Redis) is widely in place of their self-managed equivalents for in-memory caching. Aurora's automation and serverless scalability make it Zynga’s first choice for new services using relational databases.