VelesDB Benchmarks — VelesDB vs Specialist Databases

Fair benchmark suite comparing VelesDB (multi-model: vector + graph + columnar) against specialist databases on their home turf.

Fairness Guarantees

• All engines run in Docker — same isolation, same overhead
• All accessed via HTTP/network from the same Python process
• Same dataset loaded into all engines
• Same LIMIT on both sides (equal result volume)
• Warmup rounds before measurement
• p50/p99 latency reported

Test Environment

Parameter	Value
CPU	Intel Core i9-14900KF (24 cores, 32 threads, AVX2)
RAM	64 GB DDR5
OS	Windows 11 Pro + WSL2 Ubuntu 24.04
Storage	NVMe SSD
Runtime	All engines in Docker containers

Engine Versions (pinned in docker-compose.yml)

Engine	Image
VelesDB	Built from source (velesdb-core/Dockerfile)
ClickHouse	clickhouse/clickhouse-server:24.12-alpine
Qdrant	qdrant/qdrant:v1.13.2
Memgraph	memgraph/memgraph:2.21.1

Quick Start

# 1. Setup (Python venv + Docker build + start all engines)
bash setup.sh

# 2. Activate venv
source .venv/bin/activate

# 3. Run benchmarks
python3 bench_vector.py          # Vector search vs Qdrant (~5 min)
python3 bench_graph.py           # Graph traversal vs Memgraph (~3 min)
python3 bench_multicolumn.py     # Columnar queries vs ClickHouse (~2 min)
python3 bench_clickbench.py      # ClickBench adapted vs ClickHouse (~15 min)
python3 bench_hybrid.py          # Hybrid multi-paradigm (~5 min)
python3 bench_full_audit.py      # Quick audit (vector + graph)

# JSON output for CI/automation
python3 bench_vector.py --json > results/vector.json

Manual Docker Management

# Start all engines
docker compose up -d

# Check health
docker compose ps

# Rebuild VelesDB after code changes
docker compose build velesdb
docker compose up -d velesdb

# View logs
docker compose logs velesdb
docker compose logs clickhouse

# Stop all
docker compose down

# Clean volumes (reset all data)
docker compose down -v

Benchmarks

Benchmark	VelesDB vs	What it measures
bench_vector.py	Qdrant	ANN search (SIFT1M), recall@k, QPS
bench_graph.py	Memgraph	BFS/DFS traversal, pattern matching
bench_multicolumn.py	ClickHouse	Multi-predicate filters, projections
bench_clickbench.py	ClickHouse	Real ClickBench queries (1M rows)
bench_hybrid.py	CH+Qdrant+igraph	Multi-paradigm hybrid queries
bench_full_audit.py	All	Quick audit across all paradigms

License

MIT