Skip to content
db-anti-patterns logo

Database Anti-Patterns Detection

db-anti-patterns

Detection rules and grep patterns for database performance anti-patterns. Use when scanning codebase for N+1 queries, sequential queries, or connection pool issues.

SKILL.md

Full skill instructions

Database Anti-Patterns Detection

Detection rules and grep patterns for identifying database performance anti-patterns in code.

When to Use This Skill

  • Scanning codebase for performance issues
  • Code review for database patterns
  • Used by db-performance-agent for automated detection

Anti-Pattern Categories

1. N+1 Query Patterns (CRITICAL)

Queries executed inside loops - causes O(n) database calls.

Detection Patterns:

// Pattern 1: await inside for loop
for (const item of items) {
  await supabase.from('table')...  // N+1!
}

// Pattern 2: await inside forEach
items.forEach(async (item) => {
  await supabase.from('table')...  // N+1!
});

// Pattern 3: await inside map
await Promise.all(items.map(async (item) => {
  await supabase.from('table')...  // N+1 even with Promise.all!
}));

// Pattern 4: count queries in loop
for (const item of items) {
  const { count } = await supabase.from('x').select('id', { count: 'exact' })...
}

Grep Patterns:

# For loops with await supabase
grep -Pzo 'for\s*\([^)]+\)\s*\{[^}]*await[^}]*\.from\(' --include="*.ts"

# forEach with async
grep -n 'forEach\s*\(\s*async' --include="*.ts"

# map with nested await from()
grep -n '\.map\s*\(\s*async.*await.*\.from\(' --include="*.ts"

Severity: CRITICAL Impact: 50-500+ queries per request Auto-fixable: Yes - batch fetch + Map lookup


2. Sequential Independent Queries (HIGH)

Multiple await statements that could run in parallel.

Detection Pattern:

// Sequential (BAD)
const a = await supabase.from('table_a').select()...;
const b = await supabase.from('table_b').select()...;
const c = await supabase.from('table_c').select()...;

// Should be parallel (GOOD)
const [a, b, c] = await Promise.all([
  supabase.from('table_a').select()...,
  supabase.from('table_b').select()...,
  supabase.from('table_c').select()...,
]);

Detection Heuristic:

Look for 2+ consecutive lines matching:

  • const/​let X = await supabase.from(...)
  • With no data dependency between them

Severity: HIGH Impact: 2-5x latency increase Auto-fixable: Yes - wrap in Promise.all()


3. Unbounded Data Fetches (MEDIUM)

Queries without .limit() on tables that can grow large.

Large Tables to Check:

const LARGE_TABLES = [
  'events',
  'cast_assignments',
  'invoices',
  'invoice_line_items',
  'notifications',
  'notification_deliveries',
  'airtable_sync_changes',
  'audit_logs',
  'feedback_requests',
  'reimbursements',
  'reimbursement_line_items',
];

Detection Pattern:

// Missing limit (BAD for large tables)
await supabase.from('events').select('*')

// Should have limit or be filtered (GOOD)
await supabase.from('events').select('*').limit(100)
await supabase.from('events').select('*').eq('user_id', userId)

Grep Pattern:

# Selects on large tables without limit
grep -n "\.from\(['\"]events['\"]\)" --include="*.ts" | grep -v "\.limit\|\.eq\|\.in\|\.single"

Severity: MEDIUM Impact: Memory exhaustion, slow queries Auto-fixable: Partial - add .limit(), may need review


4. Individual Insert/​Update in Loops (HIGH)

Single-row operations that should be batched.

Detection Pattern:

// Individual inserts (BAD)
for (const item of items) {
  await supabase.from('table').insert({ ...item });
}

// Individual updates (BAD)
for (const id of ids) {
  await supabase.from('table').update({ status: 'done' }).eq('id', id);
}

// Batch operations (GOOD)
await supabase.from('table').insert(items);
await supabase.from('table').update({ status: 'done' }).in('id', ids);

Grep Pattern:

# Insert in loop
grep -Pzo 'for\s*\([^)]+\)\s*\{[^}]*\.insert\(' --include="*.ts"

# Update in loop
grep -Pzo 'for\s*\([^)]+\)\s*\{[^}]*\.update\(' --include="*.ts"

Severity: HIGH Impact: N database round-trips Auto-fixable: Yes - batch operations


5. Count Queries Instead of Aggregation (MEDIUM)

Using multiple COUNT queries instead of fetching once and aggregating.

Detection Pattern:

// Multiple count queries (BAD)
const { count: countA } = await supabase.from('x').select('id', { count: 'exact' }).eq('status', 'a');
const { count: countB } = await supabase.from('x').select('id', { count: 'exact' }).eq('status', 'b');
const { count: countC } = await supabase.from('x').select('id', { count: 'exact' }).eq('status', 'c');

// Single fetch + aggregate (GOOD)
const { data } = await supabase.from('x').select('status').in('status', ['a', 'b', 'c']);
const counts = { a: 0, b: 0, c: 0 };
for (const item of data) counts[item.status]++;

Grep Pattern:

# Multiple count queries (look for pattern of consecutive count selects)
grep -n "count: 'exact'" --include="*.ts"

Severity: MEDIUM Impact: 2-10x more queries than necessary Auto-fixable: Yes - single query + in-memory aggregation


6. Missing Promise.all for Related Lookups (MEDIUM)

Fetching the same related entity type multiple times sequentially.

Detection Pattern:

// Sequential related lookups (BAD)
const user1 = await getUser(id1);
const user2 = await getUser(id2);
const user3 = await getUser(id3);

// Batch lookup (GOOD)
const users = await getUsers([id1, id2, id3]);

Severity: MEDIUM Impact: Increased latency Auto-fixable: Sometimes - depends on function signature


Quick Reference: Detection Commands

# Find all N+1 patterns (for loops with await from)
grep -rn "for.*{" apps/​web --include="*.ts" | xargs -I {} sh -c 'grep -l "await.*\.from\(" {}'

# Find sequential queries (consecutive await from lines)
grep -n "await.*\.from\(" apps/​web --include="*.ts" | sort | uniq -c | sort -rn

# Find unbounded selects on large tables
for table in events cast_assignments invoices notifications; do
  grep -rn "\.from(['\"]$table['\"])" apps/​web --include="*.ts" | grep -v "\.limit\|\.single\|\.eq\|\.in"
done

# Find insert/​update in loops
grep -rn "for\s*(" apps/​web --include="*.ts" -A 5 | grep -E "\.(insert|update)\("

# Find multiple count queries in same file
grep -l "count: 'exact'" apps/​web --include="*.ts" -r | xargs -I {} grep -c "count: 'exact'" {} | grep -v ":1$"

Severity Levels

SeverityImpactFix Priority
CRITICAL10x+ queries, pool exhaustion riskImmediate
HIGH3-10x queries/​latencySame sprint
MEDIUM2-3x queries/​latencyNext sprint
LOWMinor inefficiencyBacklog

Files Commonly Affected

High-risk file patterns to prioritize scanning:

  1. Cron jobs: app/​api/​cron/​*/​route.ts
  2. Services with batch ops: **/​services/​*.service.ts
  3. Admin list pages: app/​admin/​**/​actions.ts
  4. Report generators: **/​reporting*.ts

Related Skills

  • db-performance-patterns - Correct patterns and fixes
  • db-performance-agent - Automated scanning and fixing

More Finance & Trading skills

ponytail-debt logo
Finance & Trading

ponytail-debt

Harvest every `ponytail:` comment in the codebase into a debt ledger, so the deliberate shortcuts and deferrals ponytail leaves behind get tracked instead of rotting into "later means never". One-shot report, changes nothing.

155.5K 27.9K
View
stripe-integration logo
Finance & Trading

stripe-integration

Stripe payment processing with checkout sessions, subscriptions, webhooks, and customer management.

40.2K 12.9K
View

Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups. Use this skill when creating financial projections, calculating burn rate or runway, modeling fundraising scenarios, or preparing investor-r...

40.2K 12K
View
stock-analysis logo
Finance & Trading

stock-analysis

Stock and cryptocurrency analysis with portfolio management and multi-dimensional scoring.

46 11.9K
View
coinglass logo
Finance & Trading

coinglass

Real-time crypto derivatives positioning, whale tracking, liquidations, and institutional ETF flows across 37 specialized tools.

27 11.5K
View

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

40.2K 10.5K
View

Finance AI tools

C

ChainClarity explains 700+ crypto whitepapers in plain English, with layered summaries, comparisons, research tools, alerts, and a $4.99 Pro plan.

Freemium
View
Finalle.ai logo
Finance

Finalle.ai

Stay Ahead with Finalle.ai: The Ultimate Financial News and Tools Platform

Free
View

AI-powered Pine Script code generator for TradingView

Paid
View
TradeUI logo
Finance

TradeUI

Empower your investment strategies with AI signals, option flow data, and advanced chart patterns.

Paid
View
D
Finance

Danelfin

Danelfin review covering its AI stock and ETF scores, rankings, portfolio tools, current pricing, strengths, risks, and alternatives for investors.

Freemium
View
E
Finance

Ellisense

A software for comprehensive market sentiment analysis.

Paid
View

'Stock Correlations' App by Freshly.ai: Reveal Stock Patterns and Trends

Free
View