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.

Benefits of AWS Cloud Databases

Power generative AI apps

Unlock high throughput and highly relevant vector search outcomes with low latency using native vector database capabilities. Integrations with Amazon Bedrock provides fully managed and automated Retrieval Augmented Generation.

Secure and resilient

Secure your applications with encryption at rest and in transit, network isolation, and more. AWS delivers resiliency with up to 99.999% availability, multi-AZ deployments, multi-Region replication, automated failovers, and more.

Performance at scale

Start small and scale with relational databases that have 3-5x higher throughput than alternatives, or non-relational databases that provide sub-millisecond to microsecond latency at any scale.

Cost effective

Lower total cost of ownership by using the right database engine for the job, and leverage innovations like serverless, I/O-Optimized for price predictability, and EC2 Graviton3 instances for additional price performance benefits.

Fully managed

Free your teams from time-consuming tasks. With proven operational excellence, AWS handles tasks like server provisioning and backups, and also provides continuous monitoring, self-healing storage, and automated scaling.

Simplicity of operations

Scale instantly using serverless with no servers to manage and zero downtime maintenance. Also, AWS zero-ETL integrations simplifies analytics, ML, and search on operational data removing the need to build or manage data pipelines.

Learn about AWS vector database capabilities

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

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IDC study shows $8.48 million average annual benefits per organization by using Amazon DynamoDB »

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Database services

Database type
Examples
AWS service
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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
Amazon RDS
Amazon Redshift
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Amazon Aurora

MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost 

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Amazon Relational Database Service (RDS)

Set up, operate, and scale a relational database in the cloud with just a few clicks

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Amazon Redshift

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

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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
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Amazon DynamoDB

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

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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 ElastiCache
Amazon MemoryDB for Redis
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Amazon MemoryDB for Redis

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

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Amazon ElastiCache

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

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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)
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Amazon DocumentDB (with MongoDB compatibility)

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

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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
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Amazon Neptune

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

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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
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Amazon Keyspaces

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

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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
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Amazon Timestream

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

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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 Ledger Database Services (QLDB)
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Amazon Quantum Ledger Database (QLDB)

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

Learn more with 10-minute step-by-step tutorials »

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.

Learn more »

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.

Learn more »

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 »