Baradb/docs/en/performance.md

BaraDB Performance Guide

Benchmark Methodology

All benchmarks are run with:

• Compiler: Nim 2.2.0 with -d:release --opt:speed
• CPU: AMD Ryzen 9 5900X (12 cores / 24 threads)
• Memory: 64 GB DDR4-3600
• Storage: Samsung 980 Pro NVMe SSD
• OS: Ubuntu 24.04 LTS

Run the full benchmark suite:

nim c -d:ssl -d:release -r benchmarks/bench_all.nim

Storage Engine Benchmarks

LSM-Tree Key-Value

Metric	Value
Write throughput	~580,000 ops/s
Read throughput	~720,000 ops/s
Average write latency	1.7 µs
Average read latency	1.4 µs
Test dataset	100,000 keys (16-byte keys, 64-byte values)

The LSM-Tree uses a 64MB MemTable, WAL fsync every write, and size-tiered compaction with 6 levels.

B-Tree Index

Metric	Value
Insert throughput	~1,200,000 ops/s
Point lookup throughput	~1,500,000 ops/s
Range scan (1000 keys)	~0.3 ms
Tree height (100K keys)	4

B-Tree nodes are 4KB with copy-on-write for MVCC compatibility.

Vector Engine Benchmarks

HNSW Index

Metric	Value
Insert (dim=128)	~45,000 vectors/s
Search top-10 (dim=128, n=10K)	~2 ms
Search top-10 (dim=128, n=100K)	~8 ms
Memory per vector (dim=128)	~580 bytes

Parameters: M=16, efConstruction=200, efSearch=64.

SIMD Distance Functions

Operation	dim=128	dim=768	dim=1536
Cosine distance	4.2M/s	850K/s	420K/s
L2 (Euclidean)	4.5M/s	920K/s	450K/s
Dot product	4.8M/s	980K/s	480K/s

SIMD uses AVX2 256-bit vectors with loop unrolling.

Quantization

Method	Accuracy Loss	Memory Reduction
Scalar 8-bit	<1%	4×
Scalar 4-bit	~3%	8×
Product Quantization (PQ16)	~5%	16×
Binary	~15%	32×

Full-Text Search Benchmarks

Metric	Value
Index throughput	~320,000 docs/s
BM25 search	~28,000 queries/s
Fuzzy search (distance=2)	~850 queries/s
Wildcard regex search	~4,200 queries/s

Test corpus: 5 unique documents × 2,000 repetitions (~50 words/doc).

Graph Engine Benchmarks

Operation	Throughput	Latency
Add node	~2.5M ops/s	0.4 µs
Add edge	~1.8M ops/s	0.55 µs
BFS (1K nodes, 5K edges)	~12K traversals/s	83 µs
DFS (1K nodes, 5K edges)	~15K traversals/s	67 µs
Dijkstra shortest path	—	~120 µs
PageRank (10 iterations)	~450 graphs/s	2.2 ms
Louvain community detection	—	~45 ms

Protocol Benchmarks

Protocol	Connections	Queries/sec	Latency p99
Binary (localhost)	1	45,000	0.4 ms
Binary (localhost)	100	380,000	1.2 ms
HTTP/REST	1	12,000	2.1 ms
HTTP/REST	100	95,000	5.8 ms
WebSocket	1	18,000	1.8 ms

Query Engine Benchmarks

Query Type	Rows	Time
Simple SELECT	100K	12 ms
SELECT + WHERE	100K	18 ms
SELECT + ORDER BY	100K	35 ms
GROUP BY + aggregates	100K	42 ms
INNER JOIN (1K × 1K)	1M result	85 ms
CTE (2 levels)	100K	28 ms
Subquery (EXISTS)	100K	22 ms

Scaling Behavior

Vertical Scaling

Cores	LSM Write	LSM Read	Vector Search
1	580K	720K	2.0 ms
4	1.9M	2.6M	1.1 ms
8	3.4M	4.8M	0.7 ms
16	5.8M	7.2M	0.5 ms

Memory Usage

Component	Base Memory	Per-Entity Overhead
LSM MemTable	64 MB (fixed)	~1.2× raw data
B-Tree	8 MB (fixed)	~8 bytes/key
HNSW index	—	~580 bytes/vector (dim=128)
Graph	—	~32 bytes/node, ~24 bytes/edge
FTS index	—	~40% of raw text
Page cache	256 MB (configurable)	—

Tuning Guide

For Write-Heavy Workloads

export BARADB_MEMTABLE_SIZE_MB=256
export BARADB_WAL_SYNC_INTERVAL_MS=10
export BARADB_COMPACTION_INTERVAL_MS=30000

For Read-Heavy Workloads

export BARADB_CACHE_SIZE_MB=1024
export BARADB_BLOOM_BITS_PER_KEY=10
export BARADB_COMPACTION_INTERVAL_MS=120000

For Vector Search

export BARADB_VECTOR_EF_CONSTRUCTION=200
export BARADB_VECTOR_EF_SEARCH=128
export BARADB_VECTOR_M=32

For Graph Analytics

export BARADB_GRAPH_PAGE_RANK_ITERATIONS=20
export BARADB_GRAPH_LOUVAIN_RESOLUTION=1.0