/database-performance

name: database-performance
description: Database access patterns for performance. Separate read/write models, avoid N+1 queries, use AsNoTracking, apply row limits, and never do application-side joins. Works with EF Core and Dapper.
invocable: false
tags: [cqrs, performance, patterns]

Database Performance Patterns

When to Use This Skill

Use this skill when:

• Designing data access layers
• Optimizing slow database queries
• Choosing between EF Core and Dapper
• Avoiding common performance pitfalls

---

Core Principles

1. **Separate read and write models** - Don't use the same types for both 2. **Think in batches** - Avoid N+1 queries 3. **Only retrieve what you need** - No SELECT * 4. **Apply row limits** - Always have a configurable Take/Limit 5. **Do joins in SQL** - Never in application code 6. **AsNoTracking for reads** - EF Core change tracking is expensive

---

Read/Write Model Separation (CQRS Pattern)

**Read and write models are fundamentally different - they have different shapes, columns, and purposes.** Don't create a single "User" entity and reuse it everywhere.

• **Read models** are denormalized, optimized for query efficiency, and return multiple projection types (UserProfile, UserSummary, UserDetailForAdmin)
• **Write models** are normalized, validation-focused, and accept strongly-typed commands (CreateUserCommand, UpdateUserCommand)

Architecture

src/
  MyApp.Data/
    Users/
      # Read side - multiple optimized projections
      IUserReadStore.cs
      PostgresUserReadStore.cs

      # Write side - command handlers
      IUserWriteStore.cs
      PostgresUserWriteStore.cs

      # Read DTOs - lightweight, denormalized
      UserProfile.cs
      UserSummary.cs

      # Write commands - validation-focused
      CreateUserCommand.cs
      UpdateUserCommand.cs
    Orders/
      IOrderReadStore.cs
      IOrderWriteStore.cs
      (similar structure...)

Read Store Interface

// Read models: Multiple specialized projections optimized for different use cases
public interface IUserReadStore
{
    // Returns detailed profile for single-user view
    Task<UserProfile?> GetByIdAsync(UserId id, CancellationToken ct = default);

    // Returns lightweight info for lookups
    Task<UserProfile?> GetByEmailAsync(EmailAddress email, CancellationToken ct = default);

    // Returns paginated summaries - only what the list view needs
    Task<IReadOnlyList<UserSummary>> GetAllAsync(int limit, UserId? cursor = null, CancellationToken ct = default);

    // Boolean query - no entity needed
    Task<bool> EmailExistsAsync(EmailAddress email, CancellationToken ct = default);
}

Write Store Interface

// Write model: Accepts strongly-typed commands, minimal return values
public interface IUserWriteStore
{
    // Returns only the created ID - caller doesn't need the full entity
    Task<UserId> CreateAsync(CreateUserCommand command, CancellationToken ct = default);

    // Update validates command, returns void (success or throws)
    Task UpdateAsync(UserId id, UpdateUserCommand command, CancellationToken ct = default);

    // Delete is simple and explicit
    Task DeleteAsync(UserId id, CancellationToken ct = default);
}

**Key structural differences illustrated:**

• Read store returns multiple different DTOs (UserProfile, UserSummary, bool flag)
• Write store returns minimal data (just UserId on create) or void
• Read queries are stateless projections - no tracking needed
• Write operations focus on command validation, not retrieving data afterwards
• Different databases/tables can back read vs write (eventual consistency pattern)

---

Always Apply Row Limits

**Never return unbounded result sets.** Every read method should have a configurable limit.

Pattern: Limit Parameter

public interface IOrderReadStore
{
    // Limit is required, not optional
    Task<IReadOnlyList<OrderSummary>> GetByCustomerAsync(
        CustomerId customerId,
        int limit,
        OrderId? cursor = null,
        CancellationToken ct = default);
}

// Implementation
public async Task<IReadOnlyList<OrderSummary>> GetByCustomerAsync(
    CustomerId customerId,
    int limit,
    OrderId? cursor = null,
    CancellationToken ct = default)
{
    await using var connection = await _dataSource.OpenConnectionAsync(ct);

    const string sql = """
        SELECT id, customer_id, total, status, created_at
        FROM orders
        WHERE customer_id = @CustomerId
        AND (@Cursor IS NULL OR created_at < (SELECT created_at FROM orders WHERE id = @Cursor))
        ORDER BY created_at DESC
        LIMIT @Limit
        """;

    var rows = await connection.QueryAsync<OrderRow>(sql, new
    {
        CustomerId = customerId.Value,
        Cursor = cursor?.Value,
        Limit = limit
    });

    return rows.Select(r => r.ToOrderSummary()).ToList();
}

EF Core with Pagination

public async Task<PaginatedList<OrderSummary>> GetOrdersAsync(
    CustomerId customerId,
    Paginator paginator,
    CancellationToken ct = default)
{
    var query = _context.Orders
        .AsNoTracking()
        .Where(o => o.CustomerId == customerId.Value)
        .OrderByDescending(o => o.CreatedAt);

    var totalCount = await query.CountAsync(ct);

    var orders = await query
        .Skip((paginator.PageNumber - 1) * paginator.PageSize)
        .Take(paginator.PageSize)  // Always limit!
        .Select(o => new OrderSummary(
            new OrderId(o.Id),
            o.Total,
            o.Status,
            o.CreatedAt))
        .ToListAsync(ct);

    return new PaginatedList<OrderSummary>(
        orders,
        totalCount,
        paginator.PageSize,
        paginator.PageNumber);
}

---

AsNoTracking for Read Queries

EF Core's change tracking is expensive. Disable it for read-only queries.

// DO: Disable tracking for reads
var users = await _context.Users
    .AsNoTracking()
    .Where(u => u.IsAct