Database Design Review Service

Why Database Design Review

Database design decisions have long-lasting consequences. A poor schema design made early becomes increasingly difficult and risky to change as data accumulates. Performance problems that emerge at scale often trace back to fundamental design choices.

Common database challenges include:

• Query performance degrading as data grows
• Schema rigidity making application changes difficult
• Data integrity issues from missing constraints
• Scalability limits from design choices that don’t scale
• Maintenance complexity from accumulated workarounds

A database design review identifies these issues and provides clear guidance for improvement.

What Gets Reviewed

Schema Design

The foundation of database quality:

Table Structure

• Table organization and naming
• Column types and sizes
• Nullable column necessity
• Default value appropriateness

Normalisation

• Normal form assessment
• Denormalisation justification
• Data duplication identification
• Update anomaly risks

Relationships

• Foreign key definitions
• Relationship cardinality
• Cascade behavior
• Orphan prevention

Constraints

• Primary key design
• Unique constraints
• Check constraints
• Data validation rules

Index Analysis

Critical for query performance:

Index Coverage

• Missing indexes on queried columns
• Composite index column order
• Index selectivity analysis
• Over-indexing detection

Index Efficiency

• Unused index identification
• Redundant index detection
• Index size vs. benefit
• Write penalty assessment

Query Support

• Covering indexes for common queries
• Sort order optimization
• Range query support
• Full-text search configuration

Query Performance

How the database is actually used:

Query Patterns

• Slow query identification
• Execution plan analysis
• Table scan detection
• Join optimization

Query Design

• Subquery vs. join decisions
• Aggregation efficiency
• LIMIT and pagination
• Lock contention

Application Interaction

• N+1 query patterns from application
• Unnecessary queries
• Connection usage
• Transaction scope

Scalability Assessment

Preparing for growth:

Data Volume

• Partition strategy needs
• Archive and purge patterns
• Historical data handling
• Growth rate impact

Read Scalability

• Read replica opportunities
• Caching layer needs
• Query distribution
• Connection pooling

Write Scalability

• Write volume handling
• Lock contention analysis
• Batch operation support
• Replication impact

Data Integrity

Ensuring data quality:

Referential Integrity

• Foreign key completeness
• Orphan record risks
• Cascade appropriateness
• Circular reference handling

Data Quality

• Constraint coverage
• Invalid state prevention
• Enum and status handling
• Date and time accuracy

Audit and History

• Change tracking needs
• Soft delete patterns
• Temporal data handling
• Audit trail completeness

Common Database Issues Found

Schema Problems

Type Issues

• VARCHAR(255) for everything
• TINYINT for boolean instead of proper type
• Decimal precision insufficient for currency
• Character set inconsistencies

Normalisation Problems

• Repeated data across tables
• Embedded lists in columns (comma-separated)
• JSON columns for relational data
• EAV patterns where tables work better

Relationship Issues

• Missing foreign keys
• Incorrect cascade rules
• Self-referencing without depth limits
• Many-to-many without proper junction tables

Index Problems

Missing Indexes

• WHERE clause columns without indexes
• JOIN columns without indexes
• ORDER BY columns not indexed
• Composite queries missing compound indexes

Index Issues

• Wrong column order in composite indexes
• Too many indexes slowing writes
• Duplicate or redundant indexes
• Partial indexes not covering queries

Performance Problems

Query Issues

• SELECT * loading unnecessary data
• Queries not using available indexes
• Subqueries that should be joins
• LIKE ‘%pattern%’ forcing table scans

Design Issues

• Hot tables with excessive contention
• Wide tables slowing full scans
• Missing summary tables
• No partition strategy for large tables

Integrity Issues

Constraint Gaps

• Foreign keys not enforced
• Valid states not constrained
• Unique data not marked unique
• Required fields allowing NULL

Review Methodology

The database review follows a systematic approach:

1. Schema Analysis — Structure, types, relationships, constraints
2. Index Audit — Coverage, efficiency, redundancy
3. Query Review — Performance, patterns, optimization
4. Scalability Assessment — Growth capacity, bottlenecks
5. Integrity Check — Constraints, referential integrity
6. Recommendations — Prioritized by impact and effort

The Review Report

You receive a comprehensive report including:

• Schema Assessment — Design quality evaluation
• Index Analysis — Coverage gaps and optimizations
• Performance Findings — Query issues with execution plans
• Scalability Evaluation — Growth constraints
• Integrity Review — Constraint and data quality gaps
• Recommendations — Prioritized improvements with migration guidance

What’s Needed for Review

To conduct a database design review:

• Schema definitions (DDL exports or migrations)
• Current index definitions
• Representative queries (from application code or slow query logs)
• Table sizes and growth patterns
• Current performance concerns

Sensitive data is not required—schema structure and query patterns are the focus.

Getting Started

To begin a database design review, provide:

• Database type and version
• Schema export or migration files
• Sample slow queries
• Current pain points
• Business context and growth expectations

A quote will be provided within 24-48 hours based on schema complexity.