Module optimization 

Performance optimization modules for orders of magnitude speedup

This module provides cutting-edge optimizations targeting 100x performance improvement over Neo4j through:

• SIMD-vectorized graph traversal
• Cache-optimized data layouts
• Custom memory allocators
• Compressed indexes
• JIT-compiled query operators
• Bloom filters for negative lookups
• Adaptive radix trees for property indexes

Re-exports

pub use adaptive_radix::AdaptiveRadixTree;

pub use adaptive_radix::ArtNode;

pub use bloom_filter::BloomFilter;

pub use bloom_filter::ScalableBloomFilter;

pub use cache_hierarchy::CacheHierarchy;

pub use cache_hierarchy::HotColdStorage;

pub use index_compression::CompressedIndex;

pub use index_compression::DeltaEncoder;

pub use index_compression::RoaringBitmapIndex;

pub use memory_pool::ArenaAllocator;

pub use memory_pool::NumaAllocator;

pub use memory_pool::QueryArena;

pub use query_jit::JitCompiler;

pub use query_jit::JitQuery;

pub use query_jit::QueryOperator;

pub use simd_traversal::SimdBfsIterator;

pub use simd_traversal::SimdDfsIterator;

pub use simd_traversal::SimdTraversal;

Modules

adaptive_radix

Adaptive Radix Tree (ART) for property indexes

bloom_filter

Bloom filters for fast negative lookups

cache_hierarchy

Cache-optimized data layouts with hot/cold data separation

index_compression

Compressed index structures for massive space savings

memory_pool

Custom memory allocators for graph query execution

query_jit

JIT compilation for hot query paths

simd_traversal

SIMD-optimized graph traversal algorithms