Engineering a Robust Node.js Database Connector

Link: https://github.com/rjaskonis/ndbc

NDBC is a Node.js library I engineered to simplify and secure database interactions for MySQL and MSSQL, showcasing my expertise in backend development and data management. The library’s architecture is designed for flexibility, performance, and reliability, abstracting the complexity of SQL operations while ensuring robust error handling and schema validation.

Dynamic Query Generation: NDBC dynamically constructs SQL queries by interpreting user inputs (e.g., columns, joins, WHERE clauses) and validating them against the database schema. This ensures only valid queries are executed, reducing errors and preventing SQL injection through parameterized queries.

Database-Agnostic Design: The library supports both MySQL and MSSQL by abstracting database-specific nuances (e.g., parameter syntax, limit clauses) into a unified interface. This is achieved through a modular reference system that adapts to the underlying database driver, ensuring portability across environments.

Schema-Driven Validation: Before executing queries, NDBC queries the database’s metadata (e.g., INFORMATION_SCHEMA for column names, types, and constraints) to validate inputs. This prevents invalid column references, enforces data type constraints (e.g., numeric fields, VARCHAR length limits), and ensures required fields are populated, enhancing reliability.

Intelligent CRUD Operations: For insert and update operations, NDBC intelligently determines whether to perform an INSERT or UPDATE by checking primary key presence and WHERE conditions. This logic leverages schema metadata to identify primary keys and validate data, streamlining database interactions.

Specialized Data Handling: The library processes complex data types, such as converting BLOBs to base64 for safe transport and formatting datetime fields using customizable patterns. This ensures compatibility with diverse application needs, like file storage or time-sensitive data processing.

Join Support: NDBC supports INNER, LEFT, and RIGHT joins, dynamically building join clauses based on user-defined relationships. It validates foreign and local columns against the schema, ensuring robust multi-table queries.

Error Management: Comprehensive error handling catches connection issues, schema mismatches, and data validation failures (e.g., missing required fields, type mismatches). Errors are returned with clear messages, aiding debugging and user feedback.

Performance Optimization: By leveraging connection pooling (for MSSQL) and efficient connection management (for MySQL), NDBC minimizes overhead. Queries are executed with timeouts to prevent hanging operations, and metadata is cached during query construction to reduce database calls.

Extensibility: The library supports custom SQL queries with parameterized inputs, allowing developers to bypass the structured interface for specialized use cases while maintaining security through parameter sanitization.

NDBC reflects my ability to design scalable, secure, and developer-friendly backend solutions. By integrating Lodash for efficient data manipulation and Moment.js for precise datetime handling, the library balances performance with usability. Its schema-driven approach and database-agnostic architecture make it a versatile tool for data-driven applications, from web backends to AI pipelines requiring robust data access.

This project demonstrates my expertise in crafting production-ready software that prioritizes security, maintainability, and developer productivity, making it an asset for clients seeking reliable database solutions.