Amazon Aurora
Amazon Aurora is a MySQL and PostgreSQL compatible relational database engine
- Distributed, fault-tolerant, self-healing storage system
- Auto-scales up to 64TB per database instance.
- Up to 15 low-latency read replicas
- Point-in-time recovery
- Continuous backup to Amazon S3
- Replication across three Availability Zones (AZs).
Amazon Relational Database Service (Amazon RDS)
Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud.
- Provides cost-efficient and resizable capacity
- Automates time-consuming administration tasks such as: hardware provisioning,
database setup, patching and backups.
- Six engines:
Amazon Aurora,PostgreSQL,MySQL,MariaDB,
Oracle Database, and SQL Server.
Amazon RDS on VMware
Amazon Relational Database Service (Amazon RDS) on VMware lets you deploy managed databases in on-premises VMware environments using the Amazon RDS technology
Achieve low cost hybrid by replicating RDS on VMware databases to RDS instances
in AWS. This could be used for disaster recovery, read replica bursting, and
optional long-term backup retention in Amazon S3.
Amazon DynamoDB
Amazon DynamoDB is a fully managed key-value and document database that can
handle more than 10 trillion requests per day and support peaks of more than
20 million requests per second. DynamoDB delivers:
- Single-digit millisecond performance at any scale.
- Multiregion, multimaster database
- Built-in security, backup and restore
- In-memory caching for internet-scale applications.
Use cases: mobile, web, gaming, ad tech, IoT, and other applications that need low-latency data access at any scale
Amazon ElastiCache
Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud.
Supports two open-source in-memory caching engines:
-
Amazon ElastiCache for Redis is a
Redis-compatiblefully managedin-memory service -
Both single-node and up to 15-shard clusters are available
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Scalability to up to 3.55 TiB of in-memory data.
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Scalable, and secure.
Use cases: high-performance use cases such as web, mobile apps, gaming, ad-tech, and IoT.
- ElastiCache for Memcached is protocol compliant with
Memcached, so
popular tools that you use today with existing Memcached environments will work seamlessly with the service.
Amazon Neptune
Amazon Neptune is a fast, reliable, fully managed graph database service that
makes it easy to build and run applications that work with highly connected datasets.
- Read replicas, point-in-time recovery,
- Continuous backup to Amazon S3
- Replication across Availability Zones.
- Support for encryption at rest.
- Supports popular graph models
Property Graphand W3C’sRDF, and their
respective query languages Apache TinkerPop Gremlin and SPARQL
Use cases: recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security.
Amazon Quantum Ledger Database (QLDB)
Amazon QLDB is a fully managed ledger database that provides a transparent,
immutable, and cryptographically verifiable transaction log owned by a central
trusted authority. Amazon QLDB tracks each and every application data change
and maintains a complete and verifiable history of changes over time.
- Provides developers with a familiar SQL-like API
- Flexible document data model
- Full support for transactions.
- Automatically scales to support the demands of your application.
Amazon Timestream
Amazon Timestream is a fast, scalable, fully managed time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day at 1/10th the cost of relational databases
Automates rollups, retention, tiering, and compression of data, so you can manage your data at the lowest possible cost.
Use cases: analyze log data for DevOps, sensor data for IoT applications, and industrial telemetry data for equipment maintenance.
Amazon DocumentDB
Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly
available, and fully managed document database service that supports MongoDB workloads.
Use your existing MongoDB drivers and tools with Amazon DocumentDB.
Use case: operating mission-critical MongoDB workloads at scale.