masstree
A high-performance concurrent ordered map for Rust. It stores keys as &[u8] and supports variable-length keys by building a trie of B+trees, based on the Masstree paper
Disclaimer: This is an independent implementation. It is not endorsed by, affiliated with, or connected to the original Masstree authors or their institutions.
Features
- Ordered map for byte keys (lexicographic ordering)
- Lock-free reads with version validation
- Concurrent inserts and deletes with fine-grained leaf locking
- Zero-copy range scans with
scan_refandscan_prefix - Memory reclamation via hyaline scheme (
seizecrate) - Lazy leaf coalescing for deleted entries
- Two node widths:
MassTree(WIDTH=24) andMassTree15(WIDTH=15)
Status
v0.5.0 — Core feature complete. Heavily tested but concurrent data structures require extensive stress testing beyond what tests (even though still quite comprehensive) provide. The unsafe code passes Miri with strict-provenance flag. It should be noted that the C++ implementation is a research project, not a library specifically developed for production usage. So it is quite possible that there are still various rare edge cases and soundness issues that still haven't been addressed.
| Feature | Status |
|---|---|
get, get_ref |
Lock-free with version validation |
insert |
Fine-grained leaf locking |
remove |
Concurrent deletion with memory reclamation |
scan, scan_ref, scan_prefix |
Zero-copy range iteration |
DoubleEndedIterator |
Reverse iteration support |
| Leaf coalescing | Lazy queue-based cleanup |
| Memory reclamation | Hyaline scheme via seize crate |
Tests: 939 tests (unit + 88 ported from C++ reference + proptests + stress tests). Miri strict provenance clean.
Not yet implemented: Entry API, Extend/FromIterator.
Install
[]
= { = "0.5.0", = ["mimalloc"] }
MSRV is Rust 1.92+ (Edition 2024).
The mimalloc feature sets the global allocator. If your project already uses a custom allocator, omit this feature.
Quick Start
use MassTree;
let tree: = new;
let guard = tree.guard;
// Insert
tree.insert_with_guard.unwrap;
tree.insert_with_guard.unwrap;
// Point lookup
assert_eq!;
// Remove
tree.remove_with_guard.unwrap;
assert_eq!;
// Range scan (zero-copy)
tree.scan_ref;
// Prefix scan
tree.scan_prefix;
Ergonomic APIs
For simpler use cases, auto-guard versions create guards internally:
use MassTree;
let tree: = new;
// Auto-guard versions (simpler but slightly more overhead per call)
tree.insert.unwrap;
tree.insert.unwrap;
assert_eq!;
assert_eq!;
assert!;
tree.remove.unwrap;
Range Iteration
use ;
let tree: = new;
let guard = tree.guard;
// Populate
for i in 0..100u64
// Iterator-based range scan
for entry in tree.range
// Full iteration
for entry in tree.iter
When to Use
May work well for:
- Long keys with shared prefixes (URLs, file paths, UUIDs)
- Range scans over ordered data
- Mixed read/write workloads
- High-contention scenarios (the trie structure helps here)
Consider alternatives for:
- Unordered point lookups →
dashmap - Pure insert-only workloads →
scc::TreeIndex - Integer keys only →
congee(ART-based) - Read-heavy with rare writes →
RwLock<BTreeMap>
Variant Selection
Two variants are provided with different performance characteristics:
| Variant | Best For |
|---|---|
MassTree15 |
Range scans, writes, shared-prefix keys, contention |
MassTree (WIDTH=24) |
Random-access reads, single-threaded point ops |
MassTree15 tends to perform better in our benchmarks due to cheaper u64 atomics and better cache utilization. Consider it for most workloads unless you have uniform random-access patterns.
use ;
// Default: WIDTH=24, Arc-based storage
let tree: = new;
// WIDTH=15, Arc-based storage (recommended for most workloads)
let tree15: = new;
// Inline storage for Copy types (no Arc overhead)
let inline: = new;
let inline15: = new;
How It Works
Masstree splits keys into 8-byte chunks, creating a trie where each node is a B+tree:
Key: "users/alice/profile" (19 bytes)
└─ Layer 0: "users/al" (8 bytes)
└─ Layer 1: "ice/prof" (8 bytes)
└─ Layer 2: "ile" (3 bytes)
Keys with shared prefixes share upper layers, making lookups efficient for hierarchical data.
Examples
The examples/ directory contains comprehensive usage examples:
Rayon Integration
MassTree works seamlessly with Rayon for parallel bulk operations:
use MassTree15Inline;
use *;
use Arc;
let tree: = new;
// Parallel bulk insert (~10M ops/sec)
.into_par_iter.for_each;
// Parallel lookups (~45M ops/sec)
let sum: u64 = .into_par_iter
.map
.sum;
Tokio Integration
MassTree is thread-safe but guards cannot be held across .await points:
use MassTree15;
use Arc;
let tree: = new;
// Spawn async tasks that share the tree
let handle = spawn;
// For CPU-intensive operations, use spawn_blocking
let tree_clone = clone;
spawn_blocking.await;
Crate Features
mimalloc— Use mimalloc as global allocator (recommended)tracing— Enable structured logging tologs/masstree.jsonl
License
MIT. See LICENSE.