Using Database

🎯 Exam Objectives

🎯

Exam Objective 1.9: Explain the importance of database concepts.

Track your learning progress! Click each objective as you master it:

Differentiate relational and non-relational database designs
Understand SQL queries and table structures (keys, rows, columns)
Compare self-managed vs. provider-managed (DBaaS) deployment options
Explain direct vs. cross-service database migration strategies

🗄️ 6.14 & 6.15 Database Types

Data is commonly stored in databases. There are two primary types, each with distinct characteristics and use cases.

Relational Databases

These databases have been around for a long time, are relatively secure, and are well understood. They use tables to store data and link table information using keys.

Column: Data attributes (e.g., Name, Address)
Row: Instances of that data (specific customer records)
Primary Key: Ensures no data in a row is duplicated (e.g., Customer_ID)
Foreign Key: Refers to primary keys in other tables to establish relationships

Customer_ID PK	Name	Address	Phone_Number	Email_Address
1000	Kai Garcia	33 First Street	(123) 456-7890	k.garcia@example.com
1001	Jane Doe	22 Second Street	(123) 890-4567	j.doe@example.com
1002	John Smith	11 Third Street	(987) 654-3210	j.smith@example.com

SELECT Customer_ID, Name FROM customers;

This query retrieves specific customer ID numbers and names from the database.

Non-Relational Databases (NoSQL)

Not all data fits neatly into tables. The prominent use of big data necessitates a different way of storing information. NoSQL solutions are designed to hold unstructured information organized by type, offering great flexibility, application scalability, and rapid data growth.

Four Common NoSQL Types:

📄

Document-oriented

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Key-value

📊

Wide column

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Graph stores

💡 Ideal Use Cases: Storing social media posts (user profiles, likes, images, video) or IoT device data from farms (temperature, humidity, soil hydration) where the data structure is less predictable.

Cloud Service Provider Examples

Azure: MS SQL, PostgreSQL, Cosmos DB AWS: Aurora, RDS, Redshift, DynamoDB GCP: Cloud SQL, Spanner, Bigtable, Firestore

☁️ 6.17 Database Deployment Options

Cloud services offer two primary database deployment options. Click on each card to explore the advantages and disadvantages.

🏢 Self-Managed Databases

Handled by internal staff, hosted on-premises, private cloud, or public cloud IaaS.

✅ Advantages

Full control of data
High flexibility
Avoids vendor lock-in
Control over DB choices

❌ Disadvantages

Significant time/resource investment
Requires deep technical skills
Long-term commitment

🛠️ Provider-Managed (DBaaS)

Database as a Service. Infrastructure and deployments managed by the CSP.

✅ Advantages

Maintenance-free / support provided
Built-in automation & scalability
Pay-as-you-go cost model
Structured deployment

❌ Disadvantages

Possible vendor lock-in
Public cloud security concerns
Fewer customization options
Data sovereignty issues

🔄 6.18 Migrate Databases

Database migrations present unique challenges compared to virtualized systems. A critical factor is availability. Most services provide replication during the transfer process so that changes written to the original database are replicated to the new host automatically, ensuring minimal downtime.

💡 Best Practice: Applications and their back-end databases should typically be migrated simultaneously. Retaining databases on-premises while moving applications to the cloud is less common and can introduce latency.

Migration Strategies

➡️

Direct Migration

Moving database contents between two providers (or private cloud) within the same database design.

Example: MS SQL Server → MS SQL Server

🔀

Cross-Service Migration

Data conversions between two different database engines.

Example: Oracle → Amazon Aurora