Project Overview

Developed OwlDB, a high-performance custom NoSQL database system built from scratch in Go, featuring a complete RESTful API interface and advanced concurrency support. The project demonstrates deep understanding of database fundamentals, distributed systems concepts, and production-grade software engineering practices.

Key Achievements

Extensible NoSQL Architecture

Designed and implemented an extensible NoSQL database architecture capable of supporting 100 concurrent connections with consistent performance. The architecture employs efficient data structures and indexing mechanisms optimized for fast read and write operations, while maintaining data integrity and ACID properties where appropriate.

RESTful API Architecture

Designed and implemented a hierarchical RESTful API supporting recursive nested structures (Database → Document → Collection → Document) with full CRUD operations at each level. The API follows RESTful principles with proper HTTP methods, status codes, and JSON formatting. Features include Server-Sent Events (SSE) for real-time subscriptions, authentication, CORS support, and comprehensive error handling with detailed logging.

High-Concurrency Request Handling

Leveraged Go's powerful concurrency features including goroutines and channels to handle high-volume requests efficiently. The implementation uses connection pooling, worker pools, and mutex-based synchronization to manage concurrent access to shared resources while preventing race conditions and deadlocks. Performance testing demonstrated linear scalability up to 100 concurrent connections with minimal latency degradation.

Comprehensive Testing Strategy

Achieved 92% code coverage through extensive unit and integration testing, significantly improving system reliability and maintainability. The test suite includes unit tests for individual components, integration tests for API endpoints, concurrency tests for race condition detection, and stress tests for performance validation under load.

Technical Implementation

Database Core

• Data Storage: Custom key-value store with B-tree indexing for efficient lookups
• Persistence: Write-ahead logging (WAL) for durability and crash recovery
• Memory Management: Efficient memory allocation with garbage collection optimization
• Query Engine: Support for basic filtering, sorting, and aggregation operations

API Layer

The API follows a hierarchical structure supporting recursive nesting: /v1/{database}/{document}/{collection}/{document}/...

Base Routes

• POST /auth: Authentication endpoint for API access
• /v1/: Main API base route for all database operations

Database Level - /v1/{database}

• PUT /v1/{database}: Create a new database
• DELETE /v1/{database}: Delete a database
• OPTIONS /v1/{database}: Get allowed methods

Document Level - /v1/{database}/{document}

• GET /v1/{database}/{document}: Retrieve a document
• GET /v1/{database}/{document}?mode=subscribe: Subscribe to document updates (SSE)
• PUT /v1/{database}/{document}: Create or update a document
• PATCH /v1/{database}/{document}: Partially update a document
• DELETE /v1/{database}/{document}: Delete a document
• OPTIONS /v1/{database}/{document}: Get allowed methods

Collection Level - /v1/{database}/{document}/{collection}/

• GET /v1/{database}/{document}/{collection}/: Get collection documents
• GET .../collection/?mode=subscribe&interval=[low,high]: Subscribe with interval filter (SSE)
• PUT /v1/{database}/{document}/{collection}/: Create a new collection
• POST /v1/{database}/{document}/{collection}/: Create document with auto-generated name
• DELETE /v1/{database}/{document}/{collection}/: Delete a collection
• OPTIONS /v1/{database}/{document}/{collection}/: Get allowed methods

Special Features

• SSE Subscriptions: Real-time updates using Server-Sent Events with ?mode=subscribe
• Interval Filters: Collection subscriptions support ?interval=[low,high] for range queries
• Authentication: All /v1/ endpoints require authentication (except OPTIONS)
• CORS Support: All endpoints support cross-origin requests with Access-Control-Allow-Origin: *
• Recursive Nesting: Documents in collections can contain nested collections indefinitely

Concurrency Architecture

• Connection Pool: Managed pool of database connections with automatic scaling
• Worker Pools: Dedicated worker goroutines for handling concurrent requests
• Read-Write Locks: Fine-grained locking strategy to maximize concurrent reads
• Request Queuing: Priority-based request queue for load balancing
• Graceful Shutdown: Clean connection termination and resource cleanup

Testing & Quality Assurance

The comprehensive testing strategy ensures high reliability and maintainability:

• Unit Tests: 200+ test cases covering individual functions and components
• Integration Tests: End-to-end API testing with realistic workloads
• Concurrency Tests: Race condition detection with Go's race detector
• Load Tests: Performance validation under 100+ concurrent connections
• Benchmark Tests: Operation latency and throughput measurements
• Error Recovery: Crash simulation and recovery validation

Performance Characteristics

• Write Throughput: 10,000+ writes per second
• Read Throughput: 50,000+ reads per second
• Average Latency: <5ms for simple queries
• Concurrent Connections: 100 connections with stable performance
• Memory Efficiency: ~50MB baseline memory footprint

Engineering Best Practices

The project demonstrates professional software engineering practices:

• Clean code architecture with separation of concerns
• Comprehensive documentation and code comments
• Error handling and logging throughout the codebase
• Configuration management with environment variables
• Version control with meaningful commit messages
• Code reviews and collaborative development workflow

Learning Outcomes

This project provided deep insights into:

• Database internals and storage engine design
• Concurrent programming patterns and synchronization primitives
• RESTful API design and implementation
• Performance optimization and profiling techniques
• Software testing methodologies and quality assurance
• Production-grade system design and deployment considerations