Types of AWS Cloud Databases: A Comprehensive Guide
AWS offers a wide range of purpose-built database services to meet the needs of modern applications. These databases can be classified into various types based on their data model, use cases, and other factors.
Relational Databases
Amazon Aurora
Amazon Aurora is a MySQL and PostgreSQL compatible relational database service. It provides the following features:
- Up to 5x better performance than MySQL
- Up to 3x better performance than PostgreSQL
- Availability of up to 99.99%
- Ability to scale up to 64 TB storage
- Point-in-time recovery up to 35 days back
You can deploy Aurora clusters across multiple Availability Zones for high availability and fault tolerance.
Some key use cases of Aurora are:
- Web and mobile applications
- Data warehousing
- E-commerce
- Financial services
Amazon RDS
Amazon RDS allows you to setup, operate, and scale relational databases in the cloud. It supports the following relational database engines:
- MySQL
- MariaDB
- PostgreSQL
- Oracle
- SQL Server
With RDS, you don’t have to worry about provisioning, configuring, and operating the database. It provides:
- Automated backups
- Continuous monitoring
- Fault tolerance with Multi-AZ deployments
- Software patching
This allows you to focus on your applications while AWS manages the databases.
Amazon Redshift
Amazon Redshift is a fully managed data warehouse service that makes it simple and cost-effective to analyze large amounts of data across your data platforms using SQL and existing business intelligence tools.
It provides fast query performance by using massively parallel processing and columnar storage.
So in summary, AWS provides three main relational database services – Amazon Aurora for general purpose relational databases, Amazon RDS for supported relational database engines, and Amazon Redshift for data warehousing.
Key-Value Databases
Amazon DynamoDB
Key-value databases like Amazon DynamoDB store data as a collection of key-value pairs. They are optimized for fast read and write operations.
Some key features:
- Single-digit millisecond latency at any scale
- Nearly unlimited throughput
- Built-in security, backup and restore capabilities
- On-demand and provisioned capacity modes
Amazon DynamoDB is a fully managed key-value and document database that provides single-digit millisecond performance at any scale.
Key-value databases are used for:
- High-traffic web applications
- E-commerce systems
- Gaming applications
DynamoDB is a great choice for applications that need consistent, single-digit millisecond latency at any scale. It is used by companies like Lyft, Airbnb, Samsung and Adobe.
In-memory Databases
Amazon ElastiCache
In-memory databases like Amazon ElastiCache store the entire database in the RAM to provide ultra-fast access speeds. They are mainly used as a cache to improve database performance.
It supports:
- Redis – A popular in-memory data store
- Memcached – A distributed memory object caching system
In-memory databases are used for:
- Caching
- Session management
- Gaming leaderboards
- Memcached – A distributed memory object caching system
ElastiCache is used for caching, session management, leaderboards, and real-time analytics. It can significantly improve performance of read-heavy applications.
Amazon ElastiCache provides fully managed in-memory caching solutions using Redis or Memcached.
Document Databases
Amazon DocumentDB
Document databases like Amazon DocumentDB (with MongoDB compatibility) store data in JSON-like documents. They are optimized for semi-structured data.
It offers:
- Up to 3x better performance than MongoDB
- Automated backups and point-in-time recovery
- Elastic scaling of storage and throughput capacity
- Read replicas for high availability and disaster recovery
Document databases are used for:
- Content management
- User profiles
- Catalogs
DocumentDB is ideal for storing JSON data and works well for use cases like catalogs, user profiles, content management and session stores.
Wide column Databases
Amazon Keyspaces
Wide column databases like Amazon Keyspaces (compatible with Apache Cassandra) store data in columns that have many rows. They are optimized for high scalability and availability.
Wide column databases are used for:
- Industrial applications
- Equipment maintenance
- Fleet management
Graph Databases
Amazon Neptune
Amazon Neptune is a fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets.
It supports:
- Property graph and RDF graph models
- TinkerPop and SPARQL graph query languages
Neptune is used for:
- Fraud detection
- Recommendation engines
- Social networking
- knowledge graphs
Time series Databases
Amazon Timestream
Time series databases like Amazon Timestream are optimized for time-stamped data. They provide fast queries over time intervals.
Time series databases are used for:
- IoT applications
- DevOps
- Industrial telemetry
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