Picking the Right Databases

How to pick right database

Depend on the question, read-heavy, write-heavy, or balanced workload? throughput needs?

How much data to store and for how long? Will it grow? Data durability?

Latency requirements?

Strong schema or flexibility? It depends on a lot of factors

RDS

Have fully managed postgresSQL / MySQl / Oracle / SQL Server / Maria DB

You will need to provision the RDS instance size and EBS volume type, but you can set up auto-scaling for storage

Read replicas for multi-AZ to give it more read capability or for another application so that it doesn't affect production access.

Use case: For storing relational databases OLTP online transactional processing like purchasing

Aurora

Compatible with Postgres and MySQL. It is AWS's proprietary database.

Data are stored in 6 replicas, across 3 AZ, highly available and have self-healing, also auto-scaling out of the box.

You can define custom endpoints for writer and reader database instances.

Aurora serverless: For unpredictable / intermittent workloads, no capacity planning

Aurora Multi-Masster: For fast failover for writers

Aurora Global: Up to 16 database read instance in each region

Cloning Aurora is much faster than snapshot restoring.

ElastiCache

In-memory data store that give you sub-milisecond latency. You need to provision EC2 instance type.

Redis give you multi-AZ and read replicas, and it is preserved when shutting down.

However, using ElastiCache you need to modify your code heavily.

ElastiCache is good for user session store.

DynamoDB

Fully managed serverless NoSQL database, millisecond latency. You can migrate MongoDB to here because it is key based as well with primary key.

Provisioned capacity: Used for smooth workload

On-demand capacity: Used for unpredictable workload

DynamoDB can replace ElastiCache as key/value store, can automatically expire data.

Highly available, multi-AZ, you can scale read/write independently.

DAX accelerator for microsecond read latency.

You can enable stream to react to database changes, insertion, update, delete and make it invoke lambda functions.

Good for schemas that are constantly changing.

S3

Key / value store, good for storing big objects. Max object size is 5 TB! Can have version capability.

DocumentDB

Aurora version of MongoDB, it is NoSQL database.

Used to store, query, and index JSON data.

Scales automatically, data replicated across 3 AZ.

Neptune

Fully managed graph database. Have edges and nodes.

Keyspaces

Managed Apache Cassandra. Serverless, scalable, highly available.

Another NoSQL distributed databases.

QLDB

Quantum ledger database. Ledger is a book recording financial transactions.

Again is highly available, serverless.

Review history of all changes made to your application. Immutable and cryptographically verifiable, basically the blockchain.

No decentralization, it is a central database

Timestream

Time + value. Basically a time series database.

Store and analyze trillions of events per day.

It is very fast if you are using time based data.