AWS Cloud Databases

High-performance, secure, and reliable foundation to power generative AI solutions and data-driven applications at any scale

Why AWS Databases?

AWS Databases offer a high-performance, secure, and reliable foundation to power generative AI solutions and data-driven applications that drive value for your business and customers. AWS high-performance databases support any workload or use case, including relational databases with 3-5x faster throughput than alternatives, purpose-built databases with microsecond latency, and built-in vector database capabilities with fastest throughput at the highest recall rates. AWS provides serverless options that remove the need to manage capacity by instantly scaling on demand. AWS Databases deliver unmatched security with encryption at rest and in transit, network isolation, authentication, resolution of anomalies, and rigorous adherence to compliance standards. They are highly reliable because the data is automatically replicated across multiple Availability Zones within an AWS Region. With 15+ database engines optimized for the application’s data model, AWS fully managed databases remove the undifferentiated heavy lifting of database administrative tasks.

Easy ways to improve price performance and optimize costs

up to 20%+

price-performance improvement with AWS Graviton3 on Amazon Aurora and Amazon RDS

up to 30%

cost savings with Amazon Aurora Optimized Reads and up to 8x improved query latency

up to 90%

cost savings with Amazon Aurora Serverless v2 and Amazon Neptune Serverless

up to 66%

cost savings with Amazon DynamoDB import from S3 vs. client-based writes with provisioned capacity

up to 72%

increased throughput and up to 71% reduction in latency with Amazon ElastiCache

up to 46%

increased throughput and up to 21% reduction in P99 latency with Amazon MemoryDB

Database services

Database type
AWS service

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, generative AI use cases (such as chatbots with Retrieval Augmented Generation, similarity search, recommendation systems, and more)

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 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, generative AI use cases (such as similarity search using DynamoDB zero-ETL integration with Amazon OpenSearch Service)

Amazon DynamoDB

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


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, generative AI use cases (such as chatbots with Retrieval Augmented Generation, semantic caching, recommendation systems, fraud detection, and more)

Amazon MemoryDB

Redis OSS-compatible, durable, in-memory database service for ultra-fast performance.


Amazon ElastiCache

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



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, generative AI use cases (such as chatbots with Retrieval Augmented Generation, similarity search, recommendation systems, and more)

Amazon DocumentDB (with MongoDB compatibility)

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



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, generative AI use cases (such as GraphRAG, enhanced fraud detection, discovery of new answers, and more)

Amazon Neptune

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

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.


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 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.

AWS database solutions encompass database migration, modernization, and workload resiliency to provide a dependable path and rapid progress towards powering modern applications.

Workload resiliency

Rely on AWS for workload resilience solutions including backup, failover, and recovery, ensuring operational continuity even with exponential data growth. AWS offers multi-region databases for reduced latency across AWS Regions while improving your disaster recovery posture.

Migration & modernization

Accelerate your migration to the cloud with solutions that offer practical approaches for assessing, planning, and building the right database migration path for your organization.

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

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

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

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