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 - High-throughput value-only scans with
scan_values(skips key materialization) - Memory reclamation via hyaline scheme (
seizecrate) - Lazy leaf coalescing for deleted entries
- High-performance inline variant
MassTree15Inline, this is only usable on Copy types.
Status
v0.7.3 — Core feature complete.
| 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 |
scan_values, scan_values_rev |
High-throughput value-only scans |
DoubleEndedIterator |
Reverse iteration support |
| Leaf coalescing | Lazy queue-based cleanup |
| Memory reclamation | Hyaline scheme via seize crate |
vs C++ Masstree (12T, 10s)
| Benchmark | Rust | C++ | Ratio |
|---|---|---|---|
| rw4 (reverse-seq) | 59.00 | 48.14 | 123% |
| same (10 hot keys) | 3.56 | 2.09 | 170% |
| rw2g98 (98% reads) | 25.81 | 23.04 | 112% |
| uscale (random 140M) | 11.05 | 10.58 | 104% |
| wscale (wide random) | 9.56 | 9.03 | 106% |
| rw1 (random insert+read) | 11.01 | 11.23 | 98% |
| rw3 (forward-seq) | 40.54 | 50.34 | 81% |
vs Rust Concurrent Maps (12T SMT)
Source:
runs/run158_read_write.txtConfig: 12 threads on 6 physical cores (SMT/hyperthreading), 200 samples.
| Benchmark | masstree15 | tree_index | skipmap | indexset | MT vs Best |
|---|---|---|---|---|---|
| 01_uniform | 49.85 | 20.64 | 14.14 | 17.73 | 2.42x |
| 02_zipfian | 43.39 | 18.38 | 14.98 | 3.03 | 2.36x |
| 03_shared_prefix | 24.86 | 15.17 | 12.98 | 16.37 | 1.52x |
| 04_high_contention | 76.28 | 16.44 | 17.85 | 1.97 | 4.27x |
| 05_large_dataset | 20.79 | 12.44 | 10.10 | 11.22 | 1.67x |
| 06_single_hot_key | 10.66 | 4.29 | 6.51 | 2.39 | 1.64x |
| 07_mixed_50_50 | 36.60 | 9.89 | 7.20 | 16.89 | 2.17x |
| 08_8byte_keys | 59.86 | 32.17 | 17.39 | 20.90 | 1.86x |
| 09_pure_read | 56.25 | 29.26 | 20.64 | 19.09 | 1.92x |
| 10_remove_heavy | 21.52 | 18.01 | 8.22 | 4.54 | 1.19x |
| 13_insert_only_fair | 37.25 | 24.25 | 16.72 | 6.12 | 1.54x |
| 14_pure_insert | 14.33 | 13.67 | 10.52 | 2.50 | 1.05x |
High-Impact Workloads (12T SMT)
Source:
runs/run154_high_impact_twig_optimization.txtConfig: 12 threads on 6 physical cores (SMT), 200 samples
Benchmarks targeting Masstree's architectural advantages: long keys, variable-length keys, hot key patterns, mixed operations, prefix queries, and deep trie traversal.
| Benchmark | masstree15 | indexset | tree_index | skipmap | MT vs Best |
|---|---|---|---|---|---|
| 01_long_keys_128b | 34.95 | 14.58 | 14.98 | 11.15 | 2.33x |
| 02_multiple_hot_keys | 40.97 | 14.24 | 12.43 | 13.26 | 2.88x |
| 03_mixed_get_insert_remove | 27.24 | 6.00 | 11.93 | 8.85 | 2.28x |
| 04_variable_long_keys | 28.17 | 9.30 | 8.29 | 7.51 | 3.03x |
| 05_prefix_queries (Kitem/s) | 426.3 | n/a | 14.56 | 140.7 | 3.02x |
| 06_deep_trie_traversal | 18.16 | 13.77 | 11.16 | 8.84 | 1.32x |
| 07_deep_trie_read_only | 27.90 | 15.05 | 17.35 | 15.28 | 1.61x |
| 08_variable_keys_arc | 29.56 | 11.13 | 11.55 | 8.46 | 2.56x |
Range Scans (6T Physical)
Source:
runs/run161_range_scan.txtConfig: Physical cores only, 100 samples, performance governor
| Benchmark | masstree15_inline | tree_index | MT vs TI |
|---|---|---|---|
| 01_sequential_full_scan | 28.42 | 13.47 | 2.11x |
| 02_reverse_scan | 27.09 | 13.59 | 1.99x |
| 03_clustered_scan | 29.54 | 13.40 | 2.20x |
| 04_sparse_scan | 29.43 | 13.39 | 2.20x |
| 05_shared_prefix_scan | 25.49 | 15.17 | 1.68x |
| 06_suffix_differ_scan | 22.21 | 15.66 | 1.42x |
| 07_hierarchical_scan | 27.12 | 15.62 | 1.74x |
| 08_adversarial_splits | 28.71 | 8.40 | 3.42x |
| 09_interleaved_scan | 25.42 | 13.55 | 1.88x |
| 10_blink_stress_scan | 29.31 | 13.58 | 2.16x |
| 11_random_keys_scan | 29.44 | 13.54 | 2.17x |
| 12_long_keys_64b_scan | 27.68 | 15.63 | 1.77x |
| 15_full_scan_aggregate | 178.1 | 83.36 | 2.14x |
| 16_insert_heavy | 26.93 | 19.02 | 1.42x |
| 17_hot_spot | 9.51 | 2.99 | 3.18x |
Range Scans (12T SMT)
Source:
runs/run161_range_scan.txtConfig: 12 threads on 6 physical cores (SMT), 100 samples
| Benchmark | masstree15_inline | tree_index | MT vs TI |
|---|---|---|---|
| 01_sequential_full_scan | 30.38 | 15.27 | 1.99x |
| 02_reverse_scan | 28.51 | 15.14 | 1.88x |
| 03_clustered_scan | 30.50 | 15.18 | 2.01x |
| 04_sparse_scan | 30.37 | 15.11 | 2.01x |
| 05_shared_prefix_scan | 26.12 | 21.48 | 1.22x |
| 06_suffix_differ_scan | 24.00 | 21.08 | 1.14x |
| 07_hierarchical_scan | 27.98 | 21.17 | 1.32x |
| 08_adversarial_splits | 29.23 | 10.04 | 2.91x |
| 09_interleaved_scan | 26.24 | 15.30 | 1.72x |
| 10_blink_stress_scan | 30.14 | 15.23 | 1.98x |
| 11_random_keys_scan | 29.70 | 15.17 | 1.96x |
| 12_long_keys_64b_scan | 28.25 | 21.33 | 1.32x |
| 15_full_scan_aggregate | 176.8 | 113.5 | 1.56x |
| 16_insert_heavy | 30.06 | 25.26 | 1.19x |
| 17_hot_spot | 9.69 | 4.04 | 2.40x |
Install
[]
= { = "0.7.3", = ["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 - Integer keys only →
congee(ART-based) - Read-heavy with rare writes →
RwLock<BTreeMap>
Type Aliases
| Type | Storage | Value Requirement |
|---|---|---|
MassTree<V> |
Inline (default) | V: InlineBits (Copy + fits in 64 bits) |
MassTree15<V> |
Arc-based | V: Send + Sync + 'static |
MassTree15Inline<V> |
True inline | V: InlineBits |
MassTree<V> is the recommended default for Copy types like u64, i32, f64, pointers, etc.
Use MassTree15<V> explicitly when you need to store non-Copy types like String.
use ;
// Default: inline storage for Copy types (recommended)
let tree: = new;
// Arc-based storage for non-Copy types
let tree_arc: = new;
// Explicit inline storage (same as MassTree)
let inline: = 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.