How to evaluate whether a database design is good or bad, with specific assessment methods and metrics

Database Design Quality Assessment

A well-designed database is the foundation of a reliable, performant, and maintainable application. This section provides comprehensive methods to evaluate database design quality.

Why Design Quality Matters

Poor Design Impact:
┌─────────────────────────────────────────────────────────────┐
│                                                             │
│   Bad Design ──► Data Anomalies ──► Application Bugs       │
│        │                                                    │
│        ├──► Performance Issues ──► Poor User Experience    │
│        │                                                    │
│        ├──► Scalability Problems ──► System Failures       │
│        │                                                    │
│        └──► Maintenance Nightmare ──► High Costs           │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Key Assessment Dimensions

Dimension	Description	Key Questions
Normalization	Data organization and redundancy	Is data properly normalized? Are there update anomalies?
Performance	Query efficiency and response time	Are queries fast? Is indexing appropriate?
Data Integrity	Correctness and consistency	Are constraints properly defined? Is data accurate?
Scalability	Growth handling capability	Can it handle 10x data? 100x users?
Maintainability	Ease of modification	How hard is it to add new features?

Assessment Methods Overview

1. Normalization Assessment

Evaluate the level of normalization and identify potential anomalies:

Check for 1NF, 2NF, 3NF, BCNF compliance
Identify update, insertion, and deletion anomalies
Balance normalization with performance needs

2. Performance Metrics Analysis

Measure and analyze key performance indicators:

Query execution time analysis
Index effectiveness evaluation
Table scan frequency monitoring
Connection pool utilization

3. Data Integrity Verification

Ensure data correctness and consistency:

Primary key and foreign key validation
Constraint coverage analysis
Orphan record detection
Data type appropriateness

Read more about Data Integrity →

4. Best Practices Checklist

Comprehensive checklist for design review:

Naming conventions
Index strategy
Security considerations
Documentation completeness

Quick Health Check

Run this diagnostic query to get a quick overview of your database health (PostgreSQL):

-- Database Health Overview
SELECT
    'Tables' as metric,
    COUNT(*) as value
FROM information_schema.tables
WHERE table_schema = 'public'

UNION ALL

SELECT
    'Indexes',
    COUNT(*)
FROM pg_indexes
WHERE schemaname = 'public'

UNION ALL

SELECT
    'Foreign Keys',
    COUNT(*)
FROM information_schema.table_constraints
WHERE constraint_type = 'FOREIGN KEY'
AND table_schema = 'public'

UNION ALL

SELECT
    'Tables without Primary Key',
    COUNT(*)
FROM information_schema.tables t
WHERE t.table_schema = 'public'
AND NOT EXISTS (
    SELECT 1 FROM information_schema.table_constraints tc
    WHERE tc.table_name = t.table_name
    AND tc.constraint_type = 'PRIMARY KEY'
);

Design Quality Scoring

A simple scoring framework to rate your database design:

Score	Rating	Description
90-100	Excellent	Well-designed, follows best practices, highly optimized
70-89	Good	Minor issues, generally well-structured
50-69	Fair	Some design flaws, needs improvement
30-49	Poor	Significant issues, refactoring recommended
0-29	Critical	Major redesign required

Scoring Criteria

Total Score = Normalization (25) + Performance (25) +
              Integrity (25) + Best Practices (25)

Normalization Score (0-25):
├── 1NF Compliance: 5 points
├── 2NF Compliance: 5 points
├── 3NF Compliance: 10 points
└── No Redundancy Issues: 5 points

Performance Score (0-25):
├── Appropriate Indexing: 10 points
├── Query Efficiency: 10 points
└── No N+1 Problems: 5 points

Integrity Score (0-25):
├── Primary Keys Defined: 5 points
├── Foreign Keys Proper: 10 points
├── Constraints Complete: 5 points
└── No Orphan Records: 5 points

Best Practices Score (0-25):
├── Naming Conventions: 5 points
├── Documentation: 5 points
├── Security Measures: 10 points
└── Scalability Ready: 5 points

Common Design Problems

Problem	Symptom	Solution
Data Redundancy	Same data in multiple places	Normalize to 3NF
Missing Indexes	Slow queries, full table scans	Add appropriate indexes
No Foreign Keys	Orphan records, data inconsistency	Define FK constraints
Poor Naming	Hard to understand schema	Adopt naming conventions
Over-normalization	Too many JOINs, slow performance	Strategic denormalization
Missing Constraints	Invalid data in database	Add CHECK, NOT NULL constraints

Design

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