AWS Cloud Databases

Modernize your data infrastructure with fully managed, purpose-built databases
Choose the right purpose-built engine

Build use case-driven, highly scalable, distributed applications suited to your specific needs. AWS offers 15+ purpose-built engines to support diverse data models, including relational, key-value, document, in-memory, graph, time series, wide column, and ledger databases.

Run fully managed databases

Free your teams from time-consuming database tasks like server provisioning, patching, and backups. AWS fully managed database services provide continuous monitoring, self-healing storage, and automated scaling to help you focus on application development.

Achieve performance at scale

Start small and scale as your applications grow with relational databases that are 3-5X faster than popular alternatives, or non-relational databases that give you microsecond to sub-millisecond latency. Match your storage and compute needs easily, often with no downtime.

Rely on high availability and security

Support multi-region, multi-primary replication, and provide full data oversight with multiple levels of security, including network isolation and end-to-end encryption. AWS databases deliver the high availability, reliability, and security you need for business-critical, enterprise workloads.

AWS Databases: Break Free to Save, Grow, and Innovate Faster (2:02)

Database services

Database type
Use cases
AWS service
Relational

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.

Traditional applications, enterprise resource planning (ERP), customer relationship management (CRM), ecommerce

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

Analyze all of your data with the fastest and most widely used cloud data warehouse

Key-value

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.

High-traffic web applications, ecommerce systems, gaming applications

Amazon DynamoDB

Get a fast, flexible, and serverless NoSQL database for any scale, to support key-value and document workloads

In-memory

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.

Caching, session management, gaming leaderboards, geospatial applications

Amazon MemoryDB for Redis

Compatible, durable, in-memory database service for ultra-fast performance.

Amazon ElastiCache

Unlock microsecond latency with a scalable caching service, compatible with Redis or Memcached.

Document

Document Database

A document database is designed to store semistructured data as JSON-like documents. These databases help developers build and update applications quickly.

Content management, catalogs, user profiles

Amazon DocumentDB (with MongoDB compatibility)

Scale JSON workloads with ease using an enterprise-ready document database service compatible with MongoDB.

Wide column

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.

High-scale industrial apps for equipment maintenance, fleet management, and route optimization

Amazon Keyspaces

Run your Apache Cassandra workloads on a scalable, highly available, and managed wide column database service.

Graph

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.

Fraud detection, social networking, recommendation engines

Amazon Neptune

Build applications that work with highly connected datasets using a fast, reliable graph database service.

Time series

Time Series Database

Time-series databases efficiently collect, synthesize, and derive insights from data that changes over time and with queries spanning time intervals.

Internet of Things (IoT) applications, DevOps, industrial telemetry

Amazon Timestream

Store and analyze trillions of events per day with a fast, scalable, and serverless time series database service.

Ledger

Ledger Database

Ledger databases provide a centralized and trusted authority to maintain a scalable, immutable, and cryptographically verifiable record of transactions for every application.

Systems of record, supply chain, registrations, banking transactions

Amazon Quantum Ledger Database (QLDB)

Provide transparent, immutable, cryptographically verifiable transaction logs with a fully managed ledger database service.

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 | Amazon MemoryDB 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
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 Quantum Ledger Database (QLDB)

Use cases

Migrate to the cloud by moving to managed AWS databases

Move to managed databases

Automate the time-consuming tasks of setting up, managing, and scaling databases. Spend more time on application development versus the undifferentiated heavy lifting of provisioning and managing databases on-premises.
Build new applications with purpose-built AWS databases

Build modern apps with purpose-built databases

Choose the database service best fit for the job to help you optimize scale, performance, and costs when designing applications. See how purpose-built databases match up with modern microservices architectures.

Modernize your legacy applications with AWS databases

Break free from legacy databases

Stop working around proprietary standards, punitive pricing terms, and frequent audits. Embrace open-source compatible cloud databases with commercial grade performance, availability, and scale at a fraction of the cost.

Samsung-logo-white

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

Learn more »

Case studies

Experian BM TM RGB

Experian uses Amazon DynamoDB and Amazon Aurora’s high availability to achieve 100 percent operation uptime.

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ae_networks_logo

A+E Networks uses serverless AWS databases to facilitate expansion by creating microservices-driven cloud-native applications.

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Pokemon_Logo

Pokémon migrated to AWS purpose-built databases to save tens of thousands of dollars per month.

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Cathay-Pacific-Logo

Cathay Pacific modernized its passenger revenue optimization system on AWS and increased performance by 20 percent.

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