The broadest selection of purpose-built databases for all your application needs
Choose from 15+ purpose-built database engines including relational, key-value, document, in-memory, graph, time series, wide column, and ledger databases. AWS’s portfolio of purpose-built databases supports diverse data models and allows you to build use case driven, highly scalable, distributed applications.
Get relational databases that are 3-5X faster than popular alternatives, or non-relational databases that give you microsecond to sub-millisecond latency. Start small and scale as your applications grow. You can scale your database's compute and storage resources easily, often with no downtime.
With AWS databases, you don’t need to worry about database management tasks such as server provisioning, patching, configuration, or backups. AWS continuously monitors your clusters to keep your workloads running with self-healing storage and automated scaling, so that you can focus on application development.
AWS databases are built for business-critical, enterprise workloads, offering high availability, reliability, and security. These databases support multi-region, multi-master replication, and provide full oversight of your data with multiple levels of security, including network isolation, and end-to-end encryption.
Database services
Relational Database
Relational databases store data with predefined schemas and relationships between them. These databases are designed to support ACID transactions, and maintain referential integrity and strong data consistency.
Amazon Aurora
MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost
Amazon Relational Database Service (RDS)
Set up, operate, and scale a relational database in the cloud with just a few clicks
Amazon Redshift
The most popular and fastest cloud data warehouse
Key-value Database
Key-value databases are optimized for common access patterns, typically to store and retrieve large volumes of data. These databases deliver quick response times, even in extreme volumes of concurrent requests.
Amazon DynamoDB
Fast and flexible NoSQL database service for any scale
In-memory Database
In-memory databases are used for applications that require real-time access to data. By storing data directly in memory, these databases deliver microsecond latency to applications for whom millisecond latency is not enough.
Amazon ElastiCache for Memcached
Managed, Memcached-compatible, in-memory store. Sub-millisecond latency to power real-time applications
Amazon ElastiCache for Redis
Redis compatible in-memory data store built for the cloud. Power real-time applications with sub-millisecond latency
Document Database
A document database is designed to store semistructured data as JSON-like documents. These databases help developers build and update applications quickly.
Amazon DocumentDB (with MongoDB compatibility)
Fast, scalable, highly available MongoDB-compatible database service
Wide Column Database
A wide column store is a type of NoSQL database. It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table.
Amazon Keyspaces (for Apache Cassandra)
Managed Cassandra-compatible database
Graph Database
Graph databases are for applications that need to navigate and query millions of relationships between highly connected graph datasets with millisecond latency at large scale.
Amazon Neptune
Fast, reliable graph database built for the cloud
Time Series Database
Time-series databases efficiently collect, synthesize, and derive insights from data that changes over time and with queries spanning time intervals.
Amazon Timestream
Fast, scalable, fully managed time series database
Ledger Database
Ledger databases provide a centralized and trusted authority to maintain a scalable, immutable, and cryptographically verifiable record of transactions for every application.
Amazon Quantum Ledger Database (QLDB)
Fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log. Owned by a central trusted authorit
Database services
| Database Type | Use Cases | AWS Service |
|---|---|---|
| Relational | Traditional applications, ERP, CRM, e-commerce | Amazon Aurora | Amazon RDS | Amazon Redshift |
| Key-value | High-traffic web apps, e-commerce systems, gaming applications | Amazon DynamoDB |
| In-memory | Caching, session management, gaming leaderboards, geospatial applications | Amazon ElastiCache for Memcached | Amazon ElastiCache for Redis |
| Document | Content management, catalogs, user profiles | Amazon DocumentDB (with MongoDB compatibility) |
| Wide-column | High scale industrial apps for equipment maintenance, fleet management, and route optimization | Amazon Keyspaces (for Apache Cassandra) |
| Graph | Fraud detection, social networking, recommendation engines | Amazon Neptune |
| Time series | IoT applications, DevOps, industrial telemetry |
Amazon Timestream |
| Ledger | Systems of record, supply chain, registrations, banking transactions | Amazon QLDB |
Use cases
AWS offers a broad range of fully managed database services that are purpose-built for every major use case
Move to managed databases
Build modern apps with purpose-built databases
AWS offers the broadest range of 15 purpose-built database services. These databases are optimized to give you the performance, scale, and availability that you need to support your most demanding workloads.
Break free from legacy databases
Break free from old‐guard databases that lock you in to proprietary technology, impose punitive licensing terms, and perform frequent audits. AWS provides open-source compatible databases that are built for the cloud with commercial grade performance, availability, and scale at a fraction of the cost.
Samsung migrated 1.1 billion users across three continents from Oracle to Amazon Aurora.
"The scalability of Amazon Aurora is the best benefit—especially if we focus on the cost. Samsung reduced monthly database costs by 44%."
- Salva Jung, Principal Architect and Engineering Manager
Case studies
A+E Networks migrated to serverless AWS databases to create microservices-driven cloud-native applications.
The Pokemon Company migrated to purpose-built AWS databases and saved tens of thousands of dollars per month.
Cathay Pacific modernized passenger revenue optimization system on AWS and increased performance by 20%.
Experian achieved 100% operation uptime by using Amazon DynamoDB and Amazon Aurora.