AWS Certified Database Certificate Theory Summary

1. Base

Organize missing content based on the following organized content

Data Type
- Structured
- Semi-structured
- Unstructured
- Each database has a suitable type for handling
Structured Data
- Data stored in table format
- Suitable for OLTP and OLAP workloads
- Generally stored in Relational Database
- Suitable for complex queries or analysis
  - Ex) Multiple table joins
Semi-structured Data
- Ordered but does not use a fixed schema
  - Ex) JSON
- Can accommodate various data types
- Generally stored in Non-relational Database
- Suitable for BigData and Low-latency applications
Unstructured Data
- Documents, images, videos…
- Stored in separate storage such as File System, Object Storage, Data Lake

Predefined schema
Supports ACID properties and join operations
Used in OLTP and OLAP environments
Ex) MySQL, PostgreSQL, MariaDB, Oracle, Microsoft SQL Server
Query performance improvement through table index creation
- Primary Index
- Secondary Index
ACID
- Atomicity : All or Nothing
- Consistency : Data must match the schema after transactions
- Isolation : Distinguished from other transactions
- Durability : Must be recoverable in case of unexpected failures

Instance Type
- On-demand
- Reserved
Storage
- Data storage capacity
- Backup capacity
- Snapshot capacity
- I/O request count
Data Transfer
- Inter-AZ traffic cost
- VPC outbound traffic cost

Default Parameter Group exists for each DB engine
Can create Custom Parameter Group by inheriting Default Parameter Group
Can apply Parameter Group to DB instances in the same region
Parameter Examples
- autocommit
- time_zone
- force_ssl
- default_storage_engine
- max_connections
Parameter Changes
- Dynamic Parameters are applied immediately upon change
- Static Parameters require DB reboot
  - Static Parameters maintain pending-reboot status before DB reboot
  - Changes to in-sync status after reboot