Performance Comparison
AxioDB is designed for embedded applications requiring local data storage with intelligent caching. It combines the simplicity of SQLite with MongoDB-style queries—no native dependencies, no SQL strings, pure JavaScript.
Traditional JSON Files
- Single JSON file storage leads to heavy Read/Write I/O
- No built-in caching mechanism
- Linear search for document retrieval
- Performance degrades with larger datasets
- No indexing system
- Manual file locking for concurrent access
AxioDB Advantages
- File-per-document storage for optimized data management
- InMemoryCache strategy for faster queries
- Auto-indexed documentId for lightning-fast searches
- Maintains performance with large datasets
- Multi-core parallelism with Worker Threads
- Built-in query operators ($gt, $lt, $regex, $in)
AxioDB vs SQLite
| Feature | SQLite | AxioDB |
|---|---|---|
| Native Dependencies | ❌ Yes (C bindings) | ✅ Pure JavaScript |
| Query Language | SQL Strings | JavaScript Objects |
| Schema Migrations | ❌ Required (ALTER TABLE) | ✅ Schema-less (optional) |
| Built-in Caching | ⚠️ Manual | ✅ InMemoryCache |
| Multi-core Processing | ❌ Single-threaded | ✅ Worker Threads |
| Built-in GUI | ❌ External tools only | ✅ Web interface included |
| Best For | 10M+ records, relational data | 10K-500K documents, embedded apps |
Performance Benchmark (DocumentId Lookup)
Fast
AxioDBO(1) with cacheSlow
JSON FilesO(n) linear scanDocument Retrieval SpeedHigher is Better
Performance Metrics
AxioDB's file-per-document architecture with InMemoryCache provides instant document retrieval by ID. Unlike traditional JSON files that require full-file parsing, or SQLite's native dependencies, AxioDB offers pure JavaScript performance with intelligent caching for embedded applications.
