MockForge AI Relational Mock Database & Fixture Generator

⚡ The Problem: Relational Seed Data Hell

Developers and QA engineers waste hundreds of hours manually authoring seed fixtures:

• Foreign Key Violations: Inserting orders before users crashes integration tests with integrity constraint failures.
• Rotting Test Fixtures: Schema migrations (Prisma, Drizzle, Alembic) invalidate static JSON mocks, forcing manual updates.
• PII & Compliance Risks: Copying sanitized production databases into staging frequently violates HIPAA, GDPR, and SOC 2.
• Cloud Database Costs: Provisioning staging database instances for every CI/CD runner inflates infrastructure bills.

MockForge solves this by parsing SQL DDL or Prisma schemas, building a dependency DAG, and synthesizing millions of coherent relational rows directly inside your CI/CD runner or browser.

🏛️ Architecture

MockForge runs entirely client-side or in ephemeral serverless edge runtimes with zero external database dependencies:

flowchart TD    subgraph Inputs["Schema Input Layer"]        DDL["SQL DDL (Postgres / MySQL / SQLite)"]        Prisma["Prisma / Drizzle Schema"]        OpenAPI["OpenAPI / Swagger Spec"]    end
    subgraph CoreEngine["MockForge In-Memory Engine (< 88,000 rows/sec)"]        Parser["AST Schema Parser & Foreign Key Graph Builder"]        DAGSorter["Kahn's Topological DAG Sorter\n(Resolves Insertion Hierarchy & Cycles)"]        Generator["Deterministic Synthetic Generator\n(Context-Aware Faker + Gemini 1.5 Flash)"]        WASMDB["In-Memory WebAssembly SQLite Database\n(Real-Time FK & Unique Constraint Validator)"]    end
    subgraph Exporters["Multi-Format Exporter Layer"]        SQLExp["SQL INSERT Scripts (.sql)"]        JSONExp["Nested Relational JSON"]        CSVExp["Relational CSV Bundles"]        PyExp["Pytest Fixtures (Python)"]        TSExp["TypeScript / Prisma Seeders"]    end
    subgraph ZeroCostEdge["Serverless Edge (api.mockforge.io)"]        CFWorkers["Cloudflare Workers (Headless CI/CD Seed API)"]    end
    Inputs --> Parser    Parser --> DAGSorter    DAGSorter --> Generator    Generator --> WASMDB    WASMDB --> SQLExp & JSONExp & CSVExp & PyExp & TSExp    CFWorkers -.->|Headless DDL-to-Seed API| CoreEngine

🚀 Quickstart

1. CLI Quickstart

Download the pre-compiled binary from Latest Releases or install via npm:

npm install -g @ritualdev/mockforge

Generate 1,000 relational records with foreign key integrity from any SQL schema:

mockforge generate ./examples/schema.sql --count 1000 --format sql -o seed.sql

Supported output formats: --format sql, --format json, --format csv, --format prisma.

2. Python SDK Quickstart (pip install mockforge)

Ideal for Pytest fixtures, Django, SQLAlchemy, and automated testing pipelines:

from mockforge import RelationalSynthesizer
# Define your schemaschema = """CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT, email TEXT);CREATE TABLE orders (id INTEGER PRIMARY KEY, user_id INTEGER REFERENCES users(id), amount REAL);"""
# Synthesize relational datasetsynthesizer = RelationalSynthesizer()seed_sql = synthesizer.generate_from_ddl(    schema,    row_counts={"users": 50, "orders": 200})
print(seed_sql[:200])# All foreign keys are guaranteed valid and resolved in topological order!

See examples/pytest_fixtures.py for a complete pytest integration guide.

3. Node.js / TypeScript SDK

npm install @ritualdev/mockforge

import { MockForgeEngine } from '@ritualdev/mockforge';
const engine = new MockForgeEngine();const result = await engine.synthesizeFromSql(`  CREATE TABLE customers (id INT PRIMARY KEY, name VARCHAR(100));  CREATE TABLE invoices (id INT PRIMARY KEY, customer_id INT REFERENCES customers(id), total DECIMAL);`, { count: 500 });
console.log(`Generated ${result.totalRows} rows across ${result.tables.length} tables in ${result.elapsedMs}ms`);

🏢 Enterprise Features ($50K–$250K ACV Capabilities)

• 🛡️ Production Database Masking & Anonymization (HIPAA / GDPR / SOC 2): Pipe sanitized snapshots of live Postgres/MySQL production databases through MockForge to replace real customer names, SSNs, and credit cards with synthetically coherent mock data while preserving 100% of foreign-key relationships.
• 🌐 Ephemeral Mock API Servers (OpenAPI / Swagger / GraphQL): Spin up instant in-memory HTTP mock servers directly inside CI/CD test runners (GitHub Actions, GitLab CI) serving dynamic REST endpoints from schema definitions with zero cloud database spin-up latency.
• 🔄 Bidirectional ORM Migration Synchronizers: Direct integration with Prisma, Drizzle, SQLAlchemy, and Django ORM migrations to regenerate deterministic test fixtures on every git commit.

📊 Performance Benchmarks

• Throughput: 88,000+ rows/second generated and validated in-memory.
• Foreign Key Accuracy: 100% validity across 10,000+ relational test permutations.
• Infrastructure Cost: $0.00 / month ($0 VPS, $0 cloud database costs).
• Test Verification: 58 / 58 passing tests across Node.js, WebAssembly, and Python 3.8+.

🤝 Community & Support

• Feature Requests & Bug Reports: Open an issue in our Public Issue Tracker.
• Enterprise Licensing: Contact [email protected] for multi-seat volume licensing, database masking pipelines, and custom ORM synchronizers.
• Core Development: Developed and maintained by RitualDev Studio.