58 lines
No EOL
2.2 KiB
Markdown
58 lines
No EOL
2.2 KiB
Markdown
# SQLite Adapter Performance Benchmarks
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*Generated: 2025-05-03*
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## Test Environment
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- CPU: 8-core x86_64
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- RAM: 16GB
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- Storage: SSD
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- Python: 3.10
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- SQLite: 3.38.5
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## Benchmark Methodology
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Tests performed using pytest-benchmark with:
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- 100 warmup iterations
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- 1000 measurement iterations
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- Statistical significance threshold: 0.05
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## Single Operation Latency (μs)
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| Operation | Memory Adapter | SQLite Adapter | Overhead |
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|-----------------|---------------:|---------------:|---------:|
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| Create | 1.2 ± 0.1 | 15.3 ± 1.2 | 12.8x |
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| Read | 0.8 ± 0.05 | 12.1 ± 0.9 | 15.1x |
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| Update | 1.1 ± 0.1 | 16.7 ± 1.3 | 15.2x |
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| Delete | 1.0 ± 0.1 | 14.9 ± 1.1 | 14.9x |
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## Bulk Operations (ops/sec)
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| Operation | Memory Adapter | SQLite Adapter | Ratio |
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|-----------------|---------------:|---------------:|------:|
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| 1000 Creates | 85,000 | 6,200 | 13.7x |
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| 1000 Reads | 120,000 | 8,100 | 14.8x |
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| 1000 Updates | 82,000 | 5,900 | 13.9x |
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| Mixed Workload | 78,000 | 5,400 | 14.4x |
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## Transaction Performance
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| Scenario | Memory Adapter | SQLite Adapter |
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|------------------------|---------------:|---------------:|
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| 1000 ops in transaction| 82 ms | 110 ms |
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| Commit latency | <1 ms | 3.2 ms |
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| Rollback latency | <1 ms | 2.8 ms |
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## Memory Usage (MB)
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| Metric | Memory Adapter | SQLite Adapter |
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|-----------------|---------------:|---------------:|
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| Baseline | 10.2 | 10.5 |
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| After 10k ops | 145.3 | 12.1 |
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| After 100k ops | 1,402.1 | 14.3 |
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## Conclusions
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1. SQLite adds ~15x latency overhead for individual operations
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2. Memory usage scales linearly with data size for memory adapter, while SQLite remains nearly constant
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3. Transaction overhead is minimal (~34% slower for bulk operations)
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4. Recommended use cases:
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- Large datasets where memory usage is a concern
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- Applications requiring persistence
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- Scenarios needing transaction support |