forge-sql-orm

v2.1.16

Published

7 days ago

Drizzle ORM integration for Atlassian @forge/sql. Provides a custom driver, schema migration, two levels of caching (local and global via @forge/kvs), optimistic locking, and query analysis.

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vzakharchenko

atlassian-forge atlassian-forge-drizzle forge-sql forge drizzle drizzle-orm drizzle-driver drizzle-custom-driver orm rovo database

Forge SQL ORM

Forge-SQL-ORM is an ORM designed for working with @forge/sql in Atlassian Forge. It is built on top of Drizzle ORM and provides advanced capabilities for working with relational databases inside Forge.

Key Features

✅ Custom Drizzle Driver for direct integration with @forge/sql
✅ Local Cache System (Level 1) for in-memory query optimization within single resolver invocation scope
✅ Global Cache System (Level 2) with cross-invocation caching, automatic cache invalidation and context-aware operations (using @forge/kvs )
✅ Performance Monitoring: Query execution metrics and analysis capabilities with automatic error analysis for timeout and OOM errors, plus scheduled slow query monitoring with execution plans
✅ Type-Safe Query Building: Write SQL queries with full TypeScript support
✅ Supports complex SQL queries with joins and filtering using Drizzle ORM
✅ Advanced Query Methods: selectFrom(), selectDistinctFrom(), selectCacheableFrom(), selectDistinctCacheableFrom() for all-column queries with field aliasing
✅ Query Execution with Metadata: executeWithMetadata() method for capturing detailed execution metrics including database execution time, response size, and query analysis capabilities with performance monitoring. Supports two modes for query plan printing: TopSlowest mode (default) and SummaryTable mode
✅ Raw SQL Execution: execute(), executeCacheable(), executeDDL(), and executeDDLActions() methods for direct SQL queries with local and global caching
✅ Common Table Expressions (CTEs): with() method for complex queries with subqueries
✅ Schema migration support, allowing automatic schema evolution
✅ Automatic entity generation from MySQL/tidb databases
✅ Automatic migration generation from MySQL/tidb databases
✅ Drop Migrations Generate a migration to drop all tables and clear migrations history for subsequent schema recreation
✅ Schema Fetching Development-only web trigger to retrieve current database schema and generate SQL statements for schema recreation
✅ Ready-to-use Migration Triggers Built-in web triggers for applying migrations, dropping tables (development-only), and fetching schema (development-only) with proper error handling and security controls
✅ Optimistic Locking Ensures data consistency by preventing conflicts when multiple users update the same record
✅ Query Plan Analysis: Detailed execution plan analysis and optimization insights
✅ Rovo Integration Secure pattern for natural-language analytics with comprehensive security validations, Row-Level Security (RLS) support, and dynamic SQL query execution

🚀 Getting Started

📖 Core Features

🗄️ Database Operations

⚡ Caching System

🔒 Advanced Features

Optimistic Locking
Rovo Integration - Secure pattern for natural-language analytics with dynamic SQL queries
Query Analysis and Performance Optimization
Automatic Error Analysis - Automatic timeout and OOM error detection with execution plans
Slow Query Monitoring - Scheduled monitoring of slow queries with execution plans
Date and Time Types

🛠️ Development Tools

📚 Examples

Simple Example
Drizzle Driver Example
Optimistic Locking Example
Dynamic Queries Example
Query Analysis Example
Organization Tracker Example
Checklist Example
Cache Example - Advanced caching capabilities with performance monitoring
Rovo Integration Example - Real-world Rovo AI agent implementation with secure natural-language analytics

📚 Reference

🚀 Quick Navigation

New to Forge-SQL-ORM? Start here:

Quick Start - Get up and running in 5 minutes
Installation - Complete setup guide
Basic Usage Examples - Simple query examples

Looking for specific features?

Global Cache System (Level 2) - Cross-invocation persistent caching
Local Cache System (Level 1) - In-memory invocation caching
Optimistic Locking - Data consistency
Rovo Integration - Secure natural-language analytics
Migration Tools - Database migrations
Query Analysis - Performance optimization

Looking for practical examples?

Simple Example - Basic ORM usage
Optimistic Locking Example - Real-world conflict handling
Organization Tracker Example - Complex relationships
Checklist Example - Jira integration
Cache Example - Advanced caching capabilities
Rovo Integration Example - Real-world Rovo AI agent with secure analytics

Usage Approaches

1. Full Forge-SQL-ORM Usage

import ForgeSQL from "forge-sql-orm";
const forgeSQL = new ForgeSQL();

Best for: Advanced features like optimistic locking, automatic versioning, and automatic field name collision prevention in complex queries.

2. Direct Drizzle Usage

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver } from "forge-sql-orm";
const db = drizzle(forgeDriver);

Best for: Simple Modify operations without optimistic locking. Note that you need to manually patch drizzle patchDbWithSelectAliased for select fields to prevent field name collisions in Atlassian Forge SQL.

3. Local Cache Optimization

import ForgeSQL from "forge-sql-orm";
const forgeSQL = new ForgeSQL();

// Optimize repeated queries within a single invocation
await forgeSQL.executeWithLocalContext(async () => {
  // Multiple queries here will benefit from local caching
  const users = await forgeSQL
    .select({ id: users.id, name: users.name })
    .from(users)
    .where(eq(users.active, true));

  // This query will use local cache (no database call)
  const cachedUsers = await forgeSQL
    .select({ id: users.id, name: users.name })
    .from(users)
    .where(eq(users.active, true));

  // Using new methods for better performance
  const usersFrom = await forgeSQL.selectFrom(users).where(eq(users.active, true));

  // This will use local cache (no database call)
  const cachedUsersFrom = await forgeSQL.selectFrom(users).where(eq(users.active, true));

  // Raw SQL with local caching
  const rawUsers = await forgeSQL.execute("SELECT id, name FROM users WHERE active = ?", [true]);
});

Best for: Performance optimization of repeated queries within resolvers or single invocation contexts.

Field Name Collision Prevention in Complex Queries

When working with complex queries involving multiple tables (joins, inner joins, etc.), Atlassian Forge SQL has a specific behavior where fields with the same name from different tables get collapsed into a single field with a null value. This is not a Drizzle ORM issue but rather a characteristic of Atlassian Forge SQL's behavior.

Forge-SQL-ORM provides two ways to handle this:

Using Forge-SQL-ORM

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL();

// Automatic field name collision prevention
await forgeSQL
  .select({ user: users, order: orders })
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));

Using Direct Drizzle

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver, patchDbWithSelectAliased } from "forge-sql-orm";

const db = patchDbWithSelectAliased(drizzle(forgeDriver));

// Manual field name collision prevention
await db
  .selectAliased({ user: users, order: orders })
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));

Important Notes

This is a specific behavior of Atlassian Forge SQL, not Drizzle ORM
For complex queries involving multiple tables, it's recommended to always specify select fields and avoid using select() without field selection
The solution automatically creates unique aliases for each field by prefixing them with the table name
This ensures that fields with the same name from different tables remain distinct in the query results

Installation

Forge-SQL-ORM is designed to work with @forge/sql and requires some additional setup to ensure compatibility within Atlassian Forge.

✅ Step 1: Install Dependencies

Basic installation (without caching):

npm install forge-sql-orm @forge/sql drizzle-orm -S

With caching support:

npm install forge-sql-orm @forge/sql @forge/kvs drizzle-orm -S

⚠️ Important for UI-Kit projects:

If you're installing forge-sql-orm in a UI-Kit project (projects using @forge/react), you may encounter peer dependency conflicts with @types/react. This is due to a conflict between @types/react@18 (required by @forge/react) and @types/react@19 (optional peer dependency from drizzle-orm via bun-types).

To resolve this, use the --legacy-peer-deps flag:

# Basic installation for UI-Kit projects
npm install forge-sql-orm @forge/sql drizzle-orm -S --legacy-peer-deps

# With caching support for UI-Kit projects
npm install forge-sql-orm @forge/sql @forge/kvs drizzle-orm -S --legacy-peer-deps

Note: The --legacy-peer-deps flag tells npm to ignore peer dependency conflicts. This is safe in this case because bun-types is an optional peer dependency and doesn't affect the functionality of forge-sql-orm in Forge environments.

This will:

Install Forge-SQL-ORM (the ORM for @forge/sql)
Install @forge/sql, the Forge database layer
Install @forge/kvs, the Forge Key-Value Store for caching (optional, only needed for caching features)
Install Drizzle ORM and its MySQL driver
Install TypeScript types for MySQL
Install forge-sql-orm-cli A command-line interface tool for managing Atlassian Forge SQL migrations and model generation with Drizzle ORM integration.

Quick Start

1. Basic Setup

import ForgeSQL from "forge-sql-orm";

// Initialize ForgeSQL
const forgeSQL = new ForgeSQL();

// Simple query
const users = await forgeSQL.select().from(users);

2. With Caching (Optional)

import ForgeSQL from "forge-sql-orm";

// Initialize with caching
const forgeSQL = new ForgeSQL({
  cacheEntityName: "cache",
  cacheTTL: 300,
});

// Cached query
const users = await forgeSQL
  .selectCacheable({ id: users.id, name: users.name })
  .from(users)
  .where(eq(users.active, true));

3. Local Cache Optimization

// Optimize repeated queries within a single invocation
await forgeSQL.executeWithLocalContext(async () => {
  const users = await forgeSQL
    .select({ id: users.id, name: users.name })
    .from(users)
    .where(eq(users.active, true));

  // This query will use local cache (no database call)
  const cachedUsers = await forgeSQL
    .select({ id: users.id, name: users.name })
    .from(users)
    .where(eq(users.active, true));

  // Using new methods for better performance
  const usersFrom = await forgeSQL.selectFrom(users).where(eq(users.active, true));

  // Raw SQL with local caching
  const rawUsers = await forgeSQL.execute("SELECT id, name FROM users WHERE active = ?", [true]);
});

4. Resolver Performance Monitoring

// Resolver with performance monitoring
resolver.define("fetch", async (req: Request) => {
  try {
    return await forgeSQL.executeWithMetadata(
      async () => {
        // Resolver logic with multiple queries
        const users = await forgeSQL.selectFrom(demoUsers);
        const orders = await forgeSQL
          .selectFrom(demoOrders)
          .where(eq(demoOrders.userId, demoUsers.id));
        return { users, orders };
      },
      async (totalDbExecutionTime, totalResponseSize, printQueriesWithPlan) => {
        const threshold = 500; // ms baseline for this resolver

        if (totalDbExecutionTime > threshold * 1.5) {
          console.warn(
            `[Performance Warning fetch] Resolver exceeded DB time: ${totalDbExecutionTime} ms`,
          );
          await printQueriesWithPlan(); // Optionally log or capture diagnostics for further analysis
        } else if (totalDbExecutionTime > threshold) {
          console.debug(`[Performance Debug fetch] High DB time: ${totalDbExecutionTime} ms`);
        }
      },
      {
        // Optional: Configure query plan printing behavior
        mode: "TopSlowest", // Print top slowest queries (default)
        topQueries: 3, // Print top 3 slowest queries
      },
    );
  } catch (e) {
    const error = e?.cause?.debug?.sqlMessage ?? e?.cause;
    console.error(error, e);
    throw error;
  }
});

Query Plan Printing Options:

The printQueriesWithPlan function supports two modes:

TopSlowest Mode (default): Prints execution plans for the slowest queries from the current resolver invocation
- mode: Set to 'TopSlowest' (default)
- topQueries: Number of top slowest queries to analyze (default: 1)
SummaryTable Mode: Uses CLUSTER_STATEMENTS_SUMMARY for query analysis
- mode: Set to 'SummaryTable'
- summaryTableWindowTime: Time window in milliseconds (default: 15000ms)
- Only works if queries are executed within the specified time window

5. Rovo Integration (Secure Analytics)

// Secure dynamic SQL queries for natural-language analytics
const rovo = forgeSQL.rovo();
const settings = await rovo
  .rovoSettingBuilder(usersTable, accountId)
  .addContextParameter(":currentUserId", accountId)
  .useRLS()
  .addRlsColumn(usersTable.id)
  .addRlsWherePart((alias) => `${alias}.${usersTable.id.name} = '${accountId}'`)
  .finish()
  .build();

const result = await rovo.dynamicIsolatedQuery(
  "SELECT id, name FROM users WHERE status = 'active' AND userId = :currentUserId",
  settings,
);

6. Next Steps

Full Installation Guide - Complete setup instructions
Core Features - Learn about key capabilities
Global Cache System (Level 2) - Cross-invocation caching features
Local Cache System (Level 1) - In-memory caching features
Rovo Integration - Secure natural-language analytics
API Reference - Complete API documentation

Drizzle Usage with forge-sql-orm

If you prefer to use Drizzle ORM with the additional features of Forge-SQL-ORM (like optimistic locking and caching), you can use the enhanced API:

import ForgeSQL from "forge-sql-orm";
const forgeSQL = new ForgeSQL();

// Versioned operations with cache management (recommended)
await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [userData]);
await forgeSQL.modifyWithVersioningAndEvictCache().updateById(updateData, Users);

// Versioned operations without cache management
await forgeSQL.modifyWithVersioning().insert(Users, [userData]);
await forgeSQL.modifyWithVersioning().updateById(updateData, Users);

// Non-versioned operations with cache management
await forgeSQL.insertAndEvictCache(Users).values(userData);
await forgeSQL.updateAndEvictCache(Users).set(updateData).where(eq(Users.id, 1));

// Basic Drizzle operations (cache context aware)
await forgeSQL.insert(Users).values(userData);
await forgeSQL.update(Users).set(updateData).where(eq(Users.id, 1));

// Direct Drizzle access
const db = forgeSQL.getDrizzleQueryBuilder();
const users = await db.select().from(users);

// Using new methods for enhanced functionality
const usersFrom = await forgeSQL.selectFrom(users).where(eq(users.active, true));

const usersDistinct = await forgeSQL.selectDistinctFrom(users).where(eq(users.active, true));

const usersCacheable = await forgeSQL.selectCacheableFrom(users).where(eq(users.active, true));

// Raw SQL execution
const rawUsers = await forgeSQL.execute("SELECT * FROM users WHERE active = ?", [true]);

// Raw SQL with caching
// ⚠️ IMPORTANT: When using executeCacheable(), all table names must be wrapped with backticks (`)
const cachedRawUsers = await forgeSQL.executeCacheable(
  "SELECT * FROM `users` WHERE active = ?",
  [true],
  300,
);

// Raw SQL with execution metadata and performance monitoring
const usersWithMetadata = await forgeSQL.executeWithMetadata(
  async () => {
    const users = await forgeSQL.selectFrom(usersTable);
    const orders = await forgeSQL
      .selectFrom(ordersTable)
      .where(eq(ordersTable.userId, usersTable.id));
    return { users, orders };
  },
  (totalDbExecutionTime, totalResponseSize, printQueriesWithPlan) => {
    const threshold = 500; // ms baseline for this resolver

    if (totalDbExecutionTime > threshold * 1.5) {
      console.warn(`[Performance Warning] Resolver exceeded DB time: ${totalDbExecutionTime} ms`);
      await printQueriesWithPlan(); // Analyze and print query execution plans
    } else if (totalDbExecutionTime > threshold) {
      console.debug(`[Performance Debug] High DB time: ${totalDbExecutionTime} ms`);
    }

    console.log(`DB response size: ${totalResponseSize} bytes`);
  },
  {
    // Optional: Configure query plan printing
    mode: "TopSlowest", // Print top slowest queries (default)
    topQueries: 2, // Print top 2 slowest queries
  },
);

// DDL operations for schema modifications
await forgeSQL.executeDDL(`
  CREATE TABLE users (
    id INT PRIMARY KEY AUTO_INCREMENT,
    name VARCHAR(255) NOT NULL,
    email VARCHAR(255) UNIQUE
  )
`);

// Execute regular SQL queries in DDL context for performance monitoring
await forgeSQL.executeDDLActions(async () => {
  // Execute regular SQL queries in DDL context for monitoring
  const slowQueries = await forgeSQL.execute(`
    SELECT * FROM INFORMATION_SCHEMA.STATEMENTS_SUMMARY 
    WHERE AVG_LATENCY > 1000000
  `);

  // Execute complex analysis queries in DDL context
  const performanceData = await forgeSQL.execute(`
    SELECT * FROM INFORMATION_SCHEMA.CLUSTER_STATEMENTS_SUMMARY_HISTORY
    WHERE SUMMARY_END_TIME > DATE_SUB(NOW(), INTERVAL 1 HOUR)
  `);

  return { slowQueries, performanceData };
});

// Common Table Expressions (CTEs)
const userStats = await forgeSQL
  .with(
    forgeSQL.selectFrom(users).where(eq(users.active, true)).as("activeUsers"),
    forgeSQL.selectFrom(orders).where(eq(orders.status, "completed")).as("completedOrders"),
  )
  .select({
    totalActiveUsers: sql`COUNT(au.id)`,
    totalCompletedOrders: sql`COUNT(co.id)`,
  })
  .from(sql`activeUsers au`)
  .leftJoin(sql`completedOrders co`, eq(sql`au.id`, sql`co.userId`));

// Rovo Integration for secure dynamic SQL queries
const rovo = forgeSQL.rovo();
const settings = await rovo
  .rovoSettingBuilder(usersTable, accountId)
  .addContextParameter(":currentUserId", accountId)
  .useRLS()
  .addRlsColumn(usersTable.id)
  .addRlsWherePart((alias) => `${alias}.${usersTable.id.name} = '${accountId}'`)
  .finish()
  .build();

const rovoResult = await rovo.dynamicIsolatedQuery(
  "SELECT id, name FROM users WHERE status = 'active' AND userId = :currentUserId",
  settings,
);

This approach gives you direct access to all Drizzle ORM features while still using the @forge/sql backend with enhanced caching and versioning capabilities.

Direct Drizzle Usage with Custom Driver

If you prefer to use Drizzle ORM directly without the additional features of Forge-SQL-ORM (like optimistic locking), you can use the custom driver:

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver, patchDbWithSelectAliased } from "forge-sql-orm";

// Initialize drizzle with the custom driver and patch it for aliased selects
const db = patchDbWithSelectAliased(drizzle(forgeDriver));

// Use drizzle directly
const users = await db.select().from(users);
const users = await db.selectAliased(getTableColumns(users)).from(users);
const users = await db.selectAliasedDistinct(getTableColumns(users)).from(users);
await db.insert(users)...;
await db.update(users)...;
await db.delete(users)...;
// Use drizzle with kvs cache
const users = await db.selectAliasedCacheable(getTableColumns(users)).from(users);
const users = await db.selectAliasedDistinctCacheable(getTableColumns(users)).from(users);
await db.insertAndEvictCache(users)...;
await db.updateAndEvictCache(users)...;
await db.deleteAndEvictCache(users)...;

// Use drizzle with kvs cache context
await forgeSQL.executeWithCacheContext(async () => {
  await db.insertWithCacheContext(users)...;
  await db.updateWithCacheContext(users)...;
  await db.deleteWithCacheContext(users)...;
  // invoke without cache
   const users = await db.selectAliasedCacheable(getTableColumns(users)).from(users);
  // Cache is cleared only once at the end for all affected tables
});

// Using new methods with direct drizzle
const usersFrom = await forgeSQL.selectFrom(users)
  .where(eq(users.active, true));

const usersDistinct = await forgeSQL.selectDistinctFrom(users)
  .where(eq(users.active, true));

const usersCacheable = await forgeSQL.selectCacheableFrom(users)
  .where(eq(users.active, true));

// Raw SQL execution
const rawUsers = await forgeSQL.execute(
  "SELECT * FROM users WHERE active = ?",
  [true]
);

// Raw SQL with caching
// ⚠️ IMPORTANT: When using executeCacheable(), all table names must be wrapped with backticks (`)
const cachedRawUsers = await forgeSQL.executeCacheable(
  "SELECT * FROM `users` WHERE active = ?",
  [true],
  300
);

// Raw SQL with execution metadata and performance monitoring
const usersWithMetadata = await forgeSQL.executeWithMetadata(
  async () => {
    const users = await forgeSQL.selectFrom(usersTable);
    const orders = await forgeSQL.selectFrom(ordersTable).where(eq(ordersTable.userId, usersTable.id));
    return { users, orders };
  },
  (totalDbExecutionTime, totalResponseSize, printQueriesWithPlan) => {
    const threshold = 500; // ms baseline for this resolver

    if (totalDbExecutionTime > threshold * 1.5) {
      console.warn(`[Performance Warning] Resolver exceeded DB time: ${totalDbExecutionTime} ms`);
      await printQueriesWithPlan(); // Analyze and print query execution plans
    } else if (totalDbExecutionTime > threshold) {
      console.debug(`[Performance Debug] High DB time: ${totalDbExecutionTime} ms`);
    }

    console.log(`DB response size: ${totalResponseSize} bytes`);
  },
  {
    // Optional: Configure query plan printing
    mode: 'TopSlowest', // Print top slowest queries (default)
    topQueries: 1, // Print top slowest query
  },
);

Setting Up Caching with @forge/kvs (Optional)

The caching system is optional and only needed if you want to use cache-related features. To enable the caching system, you need to install the required dependency and configure your manifest.

How Caching Works

To use caching, you need to use Forge-SQL-ORM methods that support cache management:

Methods that perform cache eviction after execution and in cache context (batch eviction):

forgeSQL.insertAndEvictCache()
forgeSQL.updateAndEvictCache()
forgeSQL.deleteAndEvictCache()
forgeSQL.modifyWithVersioningAndEvictCache()
forgeSQL.getDrizzleQueryBuilder().insertAndEvictCache()
forgeSQL.getDrizzleQueryBuilder().updateAndEvictCache()
forgeSQL.getDrizzleQueryBuilder().deleteAndEvictCache()

Methods that participate in cache context only (batch eviction):

All methods except the default Drizzle methods:
- forgeSQL.insert()
- forgeSQL.update()
- forgeSQL.delete()
- forgeSQL.modifyWithVersioning()
- forgeSQL.getDrizzleQueryBuilder().insertWithCacheContext()
- forgeSQL.getDrizzleQueryBuilder().updateWithCacheContext()
- forgeSQL.getDrizzleQueryBuilder().deleteWithCacheContext()

Methods do not do evict cache, better do not use with cache feature:

forgeSQL.getDrizzleQueryBuilder().insert()
forgeSQL.getDrizzleQueryBuilder().update()
forgeSQL.getDrizzleQueryBuilder().delete()

Cacheable methods:

forgeSQL.selectCacheable()
forgeSQL.selectDistinctCacheable()
forgeSQL.getDrizzleQueryBuilder().selectAliasedCacheable()
forgeSQL.getDrizzleQueryBuilder().selectAliasedDistinctCacheable()

Cache context example:

await forgeSQL.executeWithCacheContext(async () => {
  // These methods participate in batch cache clearing
  await forgeSQL.insert(Users).values(userData);
  await forgeSQL.update(Users).set(updateData).where(eq(Users.id, 1));
  await forgeSQL.delete(Users).where(eq(Users.id, 1));
  // Cache is cleared only once at the end for all affected tables
});

The diagram below shows the lifecycle of a cacheable query in Forge-SQL-ORM:

Resolver calls forge-sql-orm with a SQL query and parameters.
forge-sql-orm generates a cache key = hash(sql, parameters).
It asks @forge/kvs for an existing cached result.
- Cache hit → result is returned immediately.
- Cache miss / expired → query is executed against @forge/sql.
Fresh result is stored in @forge/kvs with TTL and returned to the caller.

The diagram below shows how Evict Cache works in Forge-SQL-ORM:

Data modification is executed through @forge/sql (e.g., UPDATE users ...).
After a successful update, forge-sql-orm queries the cache entity by using the sql field with filter.contains("users") to find affected cached queries.
The returned cache entries are deleted in batches (up to 25 per transaction).
Once eviction is complete, the update result is returned to the resolver.
Note: Expired entries are not processed here — they are cleaned up separately by the scheduled cache cleanup trigger using the expiration index.

The diagram below shows how Scheduled Expiration Cleanup works:

A periodic scheduler (Forge trigger) runs cache cleanup independently of data modifications.
forge-sql-orm queries the cache entity by the expiration index to find entries with expiration < now.
Entries are deleted in batches (up to 25 per transaction) until the page is empty; pagination is done with a cursor (e.g., 100 per page).
This keeps the cache footprint small and prevents stale data accumulation.

The diagram below shows how Cache Context works:

executeWithCacheContext(fn) lets you group multiple data modifications and perform one consolidated cache eviction at the end:

The context starts with an empty affectedTables set.
Each successful INSERT/UPDATE/DELETE inside the context registers its table name in affectedTables.
Reads inside the same context that target tables present in affectedTables will bypass the cache (read-through to SQL) to avoid serving stale data. These reads also do not write back to cache until eviction completes.
On context completion, affectedTables is de-duplicated and used to build one combined KVS query over the sql field with filter.or(filter.contains("<t1>"), filter.contains("<t2>"), ...), returning all impacted cache entries in a single scan (paged by cursor, e.g., 100/page).
Matching cache entries are deleted in batches (≤25 per transaction) until the page is exhausted; then the next page is fetched via the cursor.
Expiration is handled separately by the scheduled cleanup and is not part of the context flow.

Important Considerations

@forge/kvs Limits: Please review the official @forge/kvs quotas and limits before implementing caching.

Caching Guidelines:

Don't cache everything - be selective about what to cache
Don't cache simple and fast queries - sometimes direct query is faster than cache
Consider data size and frequency of changes
Monitor cache usage to stay within quotas
Use appropriate TTL values

⚠️ Important Cache Limitations:

Table names starting with a_: Tables whose names start with a_ (case-insensitive) are automatically ignored in cache operations. KVS Cache will not work with such tables, and they will be excluded from cache invalidation and cache key generation.

Step 1: Install Dependencies

npm install @forge/kvs -S

Step 2: Configure Manifest

Add the storage entity configuration and scheduler trigger to your manifest.yml:

modules:
  scheduledTrigger:
    - key: clear-cache-trigger
      function: clearCache
      interval: fiveMinute
  storage:
    entities:
      - name: cache
        attributes:
          sql:
            type: string
          expiration:
            type: integer
          data:
            type: string
        indexes:
          - sql
          - expiration
  sql:
    - key: main
      engine: mysql
  function:
    - key: clearCache
      handler: index.clearCache

// Example usage in your Forge app
import { clearCacheSchedulerTrigger } from "forge-sql-orm";

export const clearCache = () => {
  return clearCacheSchedulerTrigger({
    cacheEntityName: "cache",
  });
};

Step 3: Configure ORM Options

Set the cache entity name in your ForgeSQL configuration:

const options = {
  cacheEntityName: "cache", // Must match the entity name in manifest.yml
  cacheTTL: 300, // Default cache TTL in seconds (5 minutes)
  cacheWrapTable: true, // Wrap table names with backticks in cache keys
  // ... other options
};

const forgeSQL = new ForgeSQL(options);

Important Notes:

The cacheEntityName must exactly match the name in your manifest storage entities
The entity attributes (sql, expiration, data) are required for proper cache functionality
Indexes on sql and expiration improve cache lookup performance
Cache data is automatically cleaned up based on TTL settings
No additional permissions are required beyond standard Forge app permissions

Complete Setup Examples

Basic setup (without caching):

package.json:

npm install forge-sql-orm @forge/sql drizzle-orm -S
# For UI-Kit projects, use: npm install forge-sql-orm @forge/sql drizzle-orm -S --legacy-peer-deps

manifest.yml:

modules:
  sql:
    - key: main
      engine: mysql

index.ts:

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL();

// simple insert
await forgeSQL.insert(Users, [userData]);
// Use versioned operations without caching
await forgeSQL.modifyWithVersioning().insert(Users, [userData]);
const users = await forgeSQL.select({ id: Users.id });

With caching support:

npm install forge-sql-orm @forge/sql @forge/kvs drizzle-orm -S
# For UI-Kit projects, use: npm install forge-sql-orm @forge/sql @forge/kvs drizzle-orm -S --legacy-peer-deps

manifest.yml:

modules:
  scheduledTrigger:
    - key: clear-cache-trigger
      function: clearCache
      interval: fiveMinute
  storage:
    entities:
      - name: cache
        attributes:
          sql:
            type: string
          expiration:
            type: integer
          data:
            type: string
        indexes:
          - sql
          - expiration
  sql:
    - key: main
      engine: mysql
  function:
    - key: clearCache
      handler: index.clearCache

index.ts:

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL({
  cacheEntityName: "cache",
});

import { clearCacheSchedulerTrigger } from "forge-sql-orm";
import { getTableColumns } from "drizzle-orm";

export const clearCache = () => {
  return clearCacheSchedulerTrigger({
    cacheEntityName: "cache",
  });
};

// Now you can use caching features
const usersData = await forgeSQL
  .selectCacheable(getTableColumns(users))
  .from(users)
  .where(eq(users.active, true));

// simple insert
await forgeSQL.insertAndEvictCache(users, [userData]);
// Use versioned operations with caching
await forgeSQL.modifyWithVersioningAndEvictCache().insert(users, [userData]);

// use Cache Context
const data = await forgeSQL.executeWithCacheContextAndReturnValue(async () => {
  // after insert mark users to evict
  await forgeSQL.insert(users, [userData]);
  // after insertAndEvictCache mark orders to evict
  await forgeSQL.insertAndEvictCache(orders, [order1, order2]);
  // execute query and put result to local cache
  await forgeSQL
    .selectCacheable({
      userId: users.id,
      userName: users.name,
      orderId: orders.id,
      orderName: orders.name,
    })
    .from(users)
    .innerJoin(orders, eq(orders.userId, users.id))
    .where(eq(users.active, true));
  // use local cache without @forge/kvs and @forge/sql
  return await forgeSQL
    .selectCacheable({
      userId: users.id,
      userName: users.name,
      orderId: orders.id,
      orderName: orders.name,
    })
    .from(users)
    .innerJoin(orders, eq(orders.userId, users.id))
    .where(eq(users.active, true));
});
// execute query and put result to kvs cache
await forgeSQL
  .selectCacheable({
    userId: users.id,
    userName: users.name,
    orderId: orders.id,
    orderName: orders.name,
  })
  .from(users)
  .innerJoin(orders, eq(orders.userId, users.id))
  .where(eq(users.active, true));

// get result from @foge/kvs cache without real @forge/sql call
await forgeSQL
  .selectCacheable({
    userId: users.id,
    userName: users.name,
    orderId: orders.id,
    orderName: orders.name,
  })
  .from(users)
  .innerJoin(orders, eq(orders.userId, users.id))
  .where(eq(users.active, true));

// use Local Cache for performance optimization
const optimizedData = await forgeSQL.executeWithLocalCacheContextAndReturnValue(async () => {
  // First query - hits database and caches result
  const users = await forgeSQL
    .select({ id: users.id, name: users.name })
    .from(users)
    .where(eq(users.active, true));

  // Second query - uses local cache (no database call)
  const cachedUsers = await forgeSQL
    .select({ id: users.id, name: users.name })
    .from(users)
    .where(eq(users.active, true));

  // Using new methods for better performance
  const usersFrom = await forgeSQL.selectFrom(users).where(eq(users.active, true));

  // This will use local cache (no database call)
  const cachedUsersFrom = await forgeSQL.selectFrom(users).where(eq(users.active, true));

  // Raw SQL with local caching
  const rawUsers = await forgeSQL.execute("SELECT id, name FROM users WHERE active = ?", [true]);

  // Insert operation - evicts local cache
  await forgeSQL.insert(users).values({ name: "New User", active: true });

  // Third query - hits database again and caches new result
  const updatedUsers = await forgeSQL
    .select({ id: users.id, name: users.name })
    .from(users)
    .where(eq(users.active, true));

  return { users, cachedUsers, updatedUsers, usersFrom, cachedUsersFrom, rawUsers };
});

Choosing the Right Method - ForgeSQL ORM

When to Use Each Approach

| Method | Use Case | Versioning | Cache Management | | ------------------------------------- | ----------------------------------------------------------- | ---------- | -------------------- | | modifyWithVersioningAndEvictCache() | High-concurrency scenarios with Cache support | ✅ Yes | ✅ Yes | | modifyWithVersioning() | High-concurrency scenarios | ✅ Yes | Cache Context | | insertAndEvictCache() | Simple inserts | ❌ No | ✅ Yes | | updateAndEvictCache() | Simple updates | ❌ No | ✅ Yes | | deleteAndEvictCache() | Simple deletes | ❌ No | ✅ Yes | | insert/update/delete | Basic Drizzle operations | ❌ No | Cache Context | | selectFrom() | All-column queries with field aliasing | ❌ No | Local Cache | | selectDistinctFrom() | Distinct all-column queries with field aliasing | ❌ No | Local Cache | | selectCacheableFrom() | All-column queries with field aliasing and caching | ❌ No | Local + Global Cache | | selectDistinctCacheableFrom() | Distinct all-column queries with field aliasing and caching | ❌ No | Local + Global Cache | | execute() | Raw SQL queries with local caching | ❌ No | Local Cache | | executeCacheable() | Raw SQL queries with local and global caching | ❌ No | Local + Global Cache | | executeDDL() | DDL operations (CREATE, ALTER, DROP, etc.) | ❌ No | No Caching | | executeDDLActions() | Execute regular SQL queries in DDL operation context | ❌ No | No Caching | | with() | Common Table Expressions (CTEs) | ❌ No | Local Cache |

Choosing the Right Method - Direct Drizzle

When to Use Each Approach

| Method | Use Case | Versioning | Cache Management | | ---------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- | ---------- | -------------------- | | insertWithCacheContext/insertWithCacheContext/updateWithCacheContext | Basic Drizzle operations | ❌ No | Cache Context | | insertAndEvictCache() | Simple inserts without conflicts | ❌ No | ✅ Yes | | updateAndEvictCache() | Simple updates without conflicts | ❌ No | ✅ Yes | | deleteAndEvictCache() | Simple deletes without conflicts | ❌ No | ✅ Yes | | insert/update/delete | Basic Drizzle operations | ❌ No | ❌ No | | selectFrom() | All-column queries with field aliasing | ❌ No | Local Cache | | selectDistinctFrom() | Distinct all-column queries with field aliasing | ❌ No | Local Cache | | selectCacheableFrom() | All-column queries with field aliasing and caching | ❌ No | Local + Global Cache | | selectDistinctCacheableFrom() | Distinct all-column queries with field aliasing and caching | ❌ No | Local + Global Cache | | execute() | Raw SQL queries with local caching | ❌ No | Local Cache | | executeCacheable() | Raw SQL queries with local and global caching | ❌ No | Local + Global Cache | | executeWithMetadata() | Resolver-level profiling with execution metrics and configurable query plan printing (TopSlowest or SummaryTable mode) | ❌ No | Local Cache | | executeDDL() | DDL operations (CREATE, ALTER, DROP, etc.) | ❌ No | No Caching | | executeDDLActions() | Execute regular SQL queries in DDL operation context | ❌ No | No Caching | | with() | Common Table Expressions (CTEs) | ❌ No | Local Cache |

where Cache context - allows you to batch cache invalidation events and bypass cache reads for affected tables.

Step-by-Step Migration Workflow

Install CLI and setup scripts

npm install forge-sql-orm-cli -D
npm pkg set scripts.models:create="forge-sql-orm-cli generate:model --output src/entities --saveEnv"
npm pkg set scripts.migration:create="forge-sql-orm-cli migrations:create --force --output src/migration --entitiesPath src/entities"
npm pkg set scripts.migration:update="forge-sql-orm-cli migrations:update --entitiesPath src/entities --output src/migration"

(This is done only once when setting up the project)

Generate initial schema from an existing database
```
npm run models:create
```
(This will prompt for database credentials on first run and save them to .env file)
Create the first migration
```
npm run migration:create
```
(This initializes the database migration structure, also done once)
Deploy to Forge and verify that migrations work
- Deploy your Forge app with migrations.
- Run migrations using a Forge web trigger or Forge scheduler.
Modify the database (e.g., add a new column, index, etc.)
- Use DbSchema or manually alter the database schema.
Update the migration
```
npm run migration:update
```
- ⚠️ Do NOT update schema before this step!
- If schema is updated first, the migration will be empty!
Deploy to Forge and verify that the migration runs without issues
- Run the updated migration on Forge.
Update the schema
```
npm run models:create
```
Repeat steps 5-8 as needed

⚠️ WARNING:

Do NOT swap steps 7 and 5! If you update schema before generating a migration, the migration will be empty!
Always generate the migration first, then update the schema.

Drop Migrations

The Drop Migrations feature allows you to completely reset your database schema in Atlassian Forge SQL. This is useful when you need to:

Start fresh with a new schema
Reset all tables and their data
Clear migration history
Ensure your local schema matches the deployed database

Important Requirements

Before using Drop Migrations, ensure that:

Your local schema exactly matches the current database schema deployed in Atlassian Forge SQL
You have a backup of your data if needed
You understand that this operation will delete all tables and data

Usage

First, ensure your local schema matches the deployed database:
```
npm run models:create
```
Generate the drop migration:
```
npm run migration:drop
```
(Add this script to your package.json: npm pkg set scripts.migration:drop="forge-sql-orm-cli migrations:drop --entitiesPath src/entities --output src/migration")

Deploy and run the migration in your Forge app:

import migrationRunner from "./database/migration";
import { MigrationRunner } from "@forge/sql/out/migration";

const runner = new MigrationRunner();
await migrationRunner(runner);
await runner.run();

After dropping all tables, you can create a new migration to recreate the schema:
```
npm run migration:create
```
The --force parameter is already included in the script to allow creating migrations after dropping all tables.

Example Migration Output

The generated drop migration will look like this:

import { MigrationRunner } from "@forge/sql/out/migration";

export default (migrationRunner: MigrationRunner): MigrationRunner => {
    return migrationRunner
        .enqueue("v1_MIGRATION0", "ALTER TABLE `orders` DROP FOREIGN KEY `fk_orders_users`")
        .enqueue("v1_MIGRATION1", "DROP INDEX `idx_orders_user_id` ON `orders`")
        .enqueue("v1_MIGRATION2", "DROP TABLE IF EXISTS `orders`")
        .enqueue("v1_MIGRATION3", "DROP TABLE IF EXISTS `users`")
        .enqueue("MIGRATION_V1_1234567890", "DELETE FROM __migrations");
};

⚠️ Important Notes

This operation is irreversible - all data will be lost
Make sure your local schema is up-to-date with the deployed database
Consider backing up your data before running drop migrations
The migration will clear the __migrations table to allow for fresh migration history
Drop operations are performed in the correct order: first foreign keys, then indexes, then tables

Date and Time Types

When working with date and time fields in your models, you should use the custom types provided by Forge-SQL-ORM to ensure proper handling of date/time values. This is necessary because Forge SQL has specific format requirements for date/time values:

| Date type | Required Format | Example | | --------- | ------------------------------ | -------------------------- | | DATE | YYYY-MM-DD | 2024-09-19 | | TIME | HH:MM:SS[.fraction] | 06:40:34 | | TIMESTAMP | YYYY-MM-DD HH:MM:SS[.fraction] | 2024-09-19 06:40:34.999999 |

// ❌ Don't use standard Drizzle date/time types
export const testEntityTimeStampVersion = mysqlTable("test_entity", {
  id: int("id").primaryKey().autoincrement(),
  time_stamp: timestamp("times_tamp").notNull(),
  date_time: datetime("date_time").notNull(),
  time: time("time").notNull(),
  date: date("date").notNull(),
});

// ✅ Use Forge-SQL-ORM custom types instead
import {
  forgeDateTimeString,
  forgeDateString,
  forgeTimestampString,
  forgeTimeString,
} from "forge-sql-orm";

export const testEntityTimeStampVersion = mysqlTable("test_entity", {
  id: int("id").primaryKey().autoincrement(),
  time_stamp: forgeTimestampString("times_tamp").notNull(),
  date_time: forgeDateTimeString("date_time").notNull(),
  time: forgeTimeString("time").notNull(),
  date: forgeDateString("date").notNull(),
});

Why Custom Types?

The custom types in Forge-SQL-ORM handle the conversion between JavaScript Date objects and Forge SQL's required string formats automatically. Without these custom types, you would need to manually format dates like this:

// Without custom types, you'd need to do this manually:
const date = moment().format("YYYY-MM-DD");
const time = moment().format("HH:mm:ss.SSS");
const timestamp = moment().format("YYYY-MM-DDTHH:mm:ss.SSS");

Our custom types provide:

Automatic conversion between JavaScript Date objects and Forge SQL's required string formats
Consistent date/time handling across your application
Type safety for date/time fields
Proper handling of timezone conversions
Support for all Forge SQL date/time types (datetime, timestamp, date, time)

Available Custom Types

forgeDateTimeString - For datetime fields (YYYY-MM-DD HH:MM:SS[.fraction])
forgeTimestampString - For timestamp fields (YYYY-MM-DD HH:MM:SS[.fraction])
forgeDateString - For date fields (YYYY-MM-DD)
forgeTimeString - For time fields (HH:MM:SS[.fraction])

Each type ensures that the data is properly formatted according to Forge SQL's requirements while providing a clean, type-safe interface for your application code.

Connection to ORM

import ForgeSQL from "forge-sql-orm";

const forgeSQL = new ForgeSQL();

import { drizzle } from "drizzle-orm/mysql-proxy";
import { forgeDriver } from "forge-sql-orm";

// Initialize drizzle with the custom driver
const db = drizzle(forgeDriver);

// Use drizzle directly
const users = await db.select().from(users);

Fetch Data

Basic Fetch Operations

// Using forgeSQL.select()
const user = await forgeSQL.select({ user: users }).from(users);

// Using forgeSQL.selectDistinct()
const user = await forgeSQL.selectDistinct({ user: users }).from(users);

// Using forgeSQL.selectCacheable()
const user = await forgeSQL.selectCacheable({ user: users }).from(users);

// Using forgeSQL.selectFrom() - Select all columns with field aliasing
const user = await forgeSQL.selectFrom(users).where(eq(users.id, 1));

// Using forgeSQL.selectDistinctFrom() - Select distinct all columns with field aliasing
const user = await forgeSQL.selectDistinctFrom(users).where(eq(users.id, 1));

// Using forgeSQL.selectCacheableFrom() - Select all columns with field aliasing and caching
const user = await forgeSQL.selectCacheableFrom(users).where(eq(users.id, 1));

// Using forgeSQL.selectDistinctCacheableFrom() - Select distinct all columns with field aliasing and caching
const user = await forgeSQL.selectDistinctCacheableFrom(users).where(eq(users.id, 1));

// Using forgeSQL.execute() - Execute raw SQL with local caching
const user = await forgeSQL.execute("SELECT * FROM users WHERE id = ?", [1]);

// Using forgeSQL.executeCacheable() - Execute raw SQL with local and global caching
// ⚠️ IMPORTANT: When using executeCacheable(), all table names in SQL queries must be wrapped with backticks (`)
// Example: SELECT * FROM `users` WHERE id = ? (NOT: SELECT * FROM users WHERE id = ?)
const user = await forgeSQL.executeCacheable("SELECT * FROM `users` WHERE id = ?", [1], 300);

// Using forgeSQL.getDrizzleQueryBuilder()
const user = await forgeSQL.getDrizzleQueryBuilder().select().from(Users).where(eq(Users.id, 1));

// OR using direct drizzle with custom driver
const db = drizzle(forgeDriver);
const user = await db.select().from(Users).where(eq(Users.id, 1));
// Returns: { id: 1, name: "John Doe" }

// Using executeQueryOnlyOne for single result with error handling
const user = await forgeSQL
  .fetch()
  .executeQueryOnlyOne(
    forgeSQL.getDrizzleQueryBuilder().select().from(Users).where(eq(Users.id, 1)),
  );
// Returns: { id: 1, name: "John Doe" }
// Throws error if multiple records found
// Returns undefined if no records found

// Using with aliases
// With forgeSQL
const usersAlias = alias(Users, "u");
const result = await forgeSQL
  .getDrizzleQueryBuilder()
  .select({
    userId: sql < string > `${usersAlias.id} as \`userId\``,
    userName: sql < string > `${usersAlias.name} as \`userName\``,
  })
  .from(usersAlias);

// OR with direct drizzle
const db = drizzle(forgeDriver);
const result = await db
  .select({
    userId: sql < string > `${usersAlias.id} as \`userId\``,
    userName: sql < string > `${usersAlias.name} as \`userName\``,
  })
  .from(usersAlias);
// Returns: { userId: 1, userName: "John Doe" }

Complex Queries

// Using joins with automatic field name collision prevention
// With forgeSQL
const orderWithUser = await forgeSQL
  .select({ user: users, order: orders })
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));

// Using new selectFrom methods with joins
const orderWithUser = await forgeSQL
  .selectFrom(orders)
  .innerJoin(users, eq(orders.userId, users.id))
  .where(eq(orders.id, 1));

// Using selectCacheableFrom with joins and caching
const orderWithUser = await forgeSQL
  .selectCacheableFrom(orders)
  .innerJoin(users, eq(orders.userId, users.id))
  .where(eq(orders.id, 1));

// Using with() for Common Table Expressions (CTEs)
const userStats = await forgeSQL
  .with(
    forgeSQL.selectFrom(users).where(eq(users.active, true)).as("activeUsers"),
    forgeSQL.selectFrom(orders).where(eq(orders.status, "completed")).as("completedOrders"),
  )
  .select({
    totalActiveUsers: sql`COUNT(au.id)`,
    totalCompletedOrders: sql`COUNT(co.id)`,
  })
  .from(sql`activeUsers au`)
  .leftJoin(sql`completedOrders co`, eq(sql`au.id`, sql`co.userId`));

// OR with direct drizzle
const db = patchDbWithSelectAliased(drizzle(forgeDriver));
const orderWithUser = await db
  .selectAliased({ user: users, order: orders })
  .from(orders)
  .innerJoin(users, eq(orders.userId, users.id));
// Returns: {
//   user_id: 1,
//   user_name: "John Doe",
//   order_id: 1,
//   order_product: "Product 1"
// }

// Using distinct with aliases
const uniqueUsers = await db.selectAliasedDistinct({ user: users }).from(users);
// Returns unique users with aliased fields

// Using executeQueryOnlyOne for unique results
const userStats = await forgeSQL.fetch().executeQueryOnlyOne(
  forgeSQL
    .getDrizzleQueryBuilder()
    .select({
      totalUsers: sql`COUNT(*) as \`totalUsers\``,
      uniqueNames: sql`COUNT(DISTINCT name) as \`uniqueNames\``,
    })
    .from(Users),
);
// Returns: { totalUsers: 100, uniqueNames: 80 }
// Throws error if multiple records found

Raw SQL Queries

// Using executeRawSQL for direct SQL queries
const users = await forgeSQL
  .fetch()
  .executeRawSQL<Users>("SELECT * FROM users");

// Using execute() for raw SQL with local caching
const users = await forgeSQL
  .execute("SELECT * FROM users WHERE active = ?", [true]);

// Using executeCacheable() for raw SQL with local and global caching
// ⚠️ IMPORTANT: When using executeCacheable(), all table names in SQL queries must be wrapped with backticks (`)
// Example: SELECT * FROM `users` WHERE active = ? (NOT: SELECT * FROM users WHERE active = ?)
const users = await forgeSQL
  .executeCacheable("SELECT * FROM `users` WHERE active = ?", [true], 300);

// Using executeWithMetadata() for capturing execution metrics and performance monitoring
const usersWithMetadata = await forgeSQL.executeWithMetadata(
  async () => {
    const users = await forgeSQL.selectFrom(usersTable);
    const orders = await forgeSQL.selectFrom(ordersTable).where(eq(ordersTable.userId, usersTable.id));
    return { users, orders };
  },
  (totalDbExecutionTime, totalResponseSize, printQueriesWithPlan) => {
    const threshold = 500; // ms baseline for this resolver

    if (totalDbExecutionTime > threshold * 1.5) {
      console.warn(`[Performance Warning] Resolver exceeded DB time: ${totalDbExecutionTime} ms`);
      await printQueriesWithPlan(); // Analyze and print query execution plans
    } else if (totalDbExecutionTime > threshold) {
      console.debug(`[Performance Debug] High DB time: ${totalDbExecutionTime} ms`);
    }

    console.log(`DB response size: ${totalResponseSize} bytes`);
  },
  {
    // Optional: Configure query plan printing
    mode: 'TopSlowest', // Print top slowest queries (default)
    topQueries: 1, // Print top slowest query
  },
);

// Using executeDDL() for DDL operations (CREATE, ALTER, DROP, etc.)
await forgeSQL.executeDDL(`
  CREATE TABLE users (
    id INT PRIMARY KEY AUTO_INCREMENT,
    name VARCHAR(255) NOT NULL,
    email VARCHAR(255) UNIQUE
  )
`);

await forgeSQL.executeDDL(sql`
  ALTER TABLE users
  ADD COLUMN created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
`);

await forgeSQL.executeDDL("DROP TABLE IF EXISTS old_users");

// Using executeDDLActions() for executing regular SQL queries in DDL context
// This method executes a series of actions within a DDL operation context for monitoring
await forgeSQL.executeDDLActions(async () => {
  // Execute regular SQL queries in DDL context for performance monitoring
  const slowQueries = await forgeSQL.execute(`
    SELECT * FROM INFORMATION_SCHEMA.STATEMENTS_SUMMARY
    WHERE AVG_LATENCY > 1000000
  `);

  // Execute complex analysis queries in DDL context
  const performanceData = await forgeSQL.execute(`
    SELECT * FROM INFORMATION_SCHEMA.CLUSTER_STATEMENTS_SUMMARY_HISTORY
    WHERE SUMMARY_END_TIME > DATE_SUB(NOW(), INTERVAL 1 HOUR)
  `);

  return { slowQueries, performanceData };
});

// Using execute() with complex queries
const userStats = await forgeSQL
  .execute(`
    SELECT
      u.id,
      u.name,
      COUNT(o.id) as order_count,
      SUM(o.amount) as total_amount
    FROM users u
    LEFT JOIN orders o ON u.id = o.user_id
    WHERE u.active = ?
    GROUP BY u.id, u.name
  `, [true]);

Modify Operations

Forge-SQL-ORM provides multiple approaches for Modify operations, each with different characteristics:

1. Basic Drizzle Operations (Cache Context Aware)

These operations work like standard Drizzle methods but participate in cache context when used within executeWithCacheContext():

// Basic insert (participates in cache context when used within executeWithCacheContext)
await forgeSQL.insert(Users).values({ id: 1, name: "Smith" });

// Basic update (participates in cache context when used within executeWithCacheContext)
await forgeSQL.update(Users).set({ name: "Smith Updated" }).where(eq(Users.id, 1));

// Basic delete (participates in cache context when used within executeWithCacheContext)
await forgeSQL.delete(Users).where(eq(Users.id, 1));

2. Non-Versioned Operations with Cache Management

These operations don't use optimistic locking but provide cache invalidation:

// Insert without versioning but with cache invalidation
await forgeSQL.insertAndEvictCache(Users).values({ id: 1, name: "Smith" });

// Update without versioning but with cache invalidation
await forgeSQL.updateAndEvictCache(Users).set({ name: "Smith Updated" }).where(eq(Users.id, 1));

// Delete without versioning but with cache invalidation
await forgeSQL.deleteAndEvictCache(Users).where(eq(Users.id, 1));

3. Versioned Operations with Cache Management (Recommended)

These operations use optimistic locking and automatic cache invalidation:

// Insert with versioning and cache management
const userId = await forgeSQL
  .modifyWithVersioningAndEvictCache()
  .insert(Users, [{ id: 1, name: "Smith" }]);

// Bulk insert with versioning
await forgeSQL.modifyWithVersioningAndEvictCache().insert(Users, [
  { id: 2, name: "Smith" },
  { id: 3, name: "Vasyl" },
]);

// Update by ID with optimistic locking and cache invalidation
await forgeSQL
  .modifyWithVersioningAndEvictCache()
  .updateById({ id: 1, name: "Smith Updated" }, Users);

// Delete by ID with versioning and cache invalidation
await forgeSQL.modifyWithVersioningAndEvictCache().deleteById(1, Users);

4. Versioned Operations without Cache Management

These operations use optimistic locking but don't manage cache:

// Insert with versioning only (no cache management)
const userId = await forgeSQL.modifyWithVersioning().insert(Users, [{ id: 1, name: "Smith" }]);

// Update with versioning only
await forgeSQL.modifyWithVersioning().updateById({ id: 1, name: "Smith Updated" }, Users);

// Delete with versioning only
await forgeSQL.modifyWithVersioning().deleteById(1, Users);

5. Legacy Modify Operations (Removed in 2.1.x)

⚠️ BREAKING CHANGE: The crud() and modify() methods have been completely removed in version 2.1.x.

// ❌ These methods no longer exist in 2.1.x
// const userId = await forgeSQL.crud().insert(Users, [{ id: 1, name: "Smith" }]);
// await forgeSQL.crud().updateById({ id: 1, name: "Smith Updated" }, Users);
// await forgeSQL.crud().deleteById(1, Users);

// ✅ Use the new methods instead
const userId = await forgeSQL.modifyWithVersioning().insert(Users, [{ id: 1, name: "Smith" }]);
await forgeSQL.modifyWithVersioning().updateById({ id: 1, name: "Smith Updated" }, Users);
await forgeSQL.modifyWithVersioning().deleteById(1, Users);

Advanced Operations

// Insert with sequence (nextVal)
import { nextVal } from "forge-sql-orm";

const user = {
  id: nextVal("user_id_seq"),
  name: "user test",
  organization_id: 1,
};
const id = await forgeSQL.modifyWithVersioning().insert(appUser, [user]);

// Update with custom WHERE condition
await forgeSQL
  .modifyWithVersioning()
  .updateFields({ name: "New Name", age: 35 }, Users, eq(Users.email, "[email protected]"));

// Insert with duplicate handling
await forgeSQL.modifyWithVersioning().insert(
  Users,
  [
    { id: 4, name: "Smith" },
    { id: 4, name: "Vasyl" },
  ],
  true,
);

SQL Utilities

formatLimitOffset

The formatLimitOffset utility function is used to safely insert numeric values directly into SQL queries for LIMIT and OFFSET clauses. This is necessary because Atlassia

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Forge SQL ORM

Key Features

Table of Contents

🚀 Getting Started

📖 Core Features

🗄️ Database Operations

⚡ Caching System

🔒 Advanced Features

🛠️ Development Tools

📚 Examples

📚 Reference

🚀 Quick Navigation

Usage Approaches

1. Full Forge-SQL-ORM Usage

2. Direct Drizzle Usage

3. Local Cache Optimization

Field Name Collision Prevention in Complex Queries

Using Forge-SQL-ORM

Using Direct Drizzle

Important Notes

Installation

Quick Start

1. Basic Setup

2. With Caching (Optional)

3. Local Cache Optimization

4. Resolver Performance Monitoring

5. Rovo Integration (Secure Analytics)

6. Next Steps

Drizzle Usage with forge-sql-orm

Direct Drizzle Usage with Custom Driver

Setting Up Caching with @forge/kvs (Optional)

How Caching Works

Important Considerations

Step 1: Install Dependencies

Step 2: Configure Manifest

Step 3: Configure ORM Options

Complete Setup Examples

Choosing the Right Method - ForgeSQL ORM

When to Use Each Approach

Choosing the Right Method - Direct Drizzle

When to Use Each Approach

Step-by-Step Migration Workflow

Drop Migrations

Important Requirements

Usage

Example Migration Output

⚠️ Important Notes

Date and Time Types

Why Custom Types?

Available Custom Types

Connection to ORM

Fetch Data

Basic Fetch Operations

Complex Queries

Raw SQL Queries

Modify Operations

1. Basic Drizzle Operations (Cache Context Aware)

2. Non-Versioned Operations with Cache Management

3. Versioned Operations with Cache Management (Recommended)

4. Versioned Operations without Cache Management

5. Legacy Modify Operations (Removed in 2.1.x)

Advanced Operations

SQL Utilities

formatLimitOffset