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fixed error comparing hex/binary in pubkey white/blacklist, complete neo4j and tests"
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mleku
2025-11-19 11:25:38 +00:00
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cmd/benchmark/README.md
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A comprehensive benchmarking system for testing and comparing the performance of multiple Nostr relay implementations, including:
- **next.orly.dev** (this repository) - Badger and DGraph backend variants
- **next.orly.dev** (this repository) - Badger, DGraph, and Neo4j backend variants
- **Khatru** - SQLite and Badger variants
- **Relayer** - Basic example implementation
- **Strfry** - C++ LMDB-based relay
@@ -95,14 +95,16 @@ ls reports/run_YYYYMMDD_HHMMSS/
| ------------------ | ---- | ----------------------------------------- |
| next-orly-badger | 8001 | This repository's Badger relay |
| next-orly-dgraph | 8007 | This repository's DGraph relay |
| next-orly-neo4j | 8008 | This repository's Neo4j relay |
| dgraph-zero | 5080 | DGraph cluster coordinator |
| dgraph-alpha | 9080 | DGraph data node |
| neo4j | 7474/7687 | Neo4j graph database |
| khatru-sqlite | 8002 | Khatru with SQLite backend |
| khatru-badger | 8003 | Khatru with Badger backend |
| relayer-basic | 8004 | Basic relayer example |
| strfry | 8005 | Strfry C++ LMDB relay |
| nostr-rs-relay | 8006 | Rust SQLite relay |
| benchmark-runner | - | Orchestrates tests and aggregates results |
| nostr-rs-relay | 8006 | Rust SQLite relay |
| benchmark-runner | - | Orchestrates tests and aggregates results |
### File Structure
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## Database Backend Comparison
The benchmark suite includes **next.orly.dev** with two different database backends to compare architectural approaches:
The benchmark suite includes **next.orly.dev** with three different database backends to compare architectural approaches:
### Badger Backend (next-orly-badger)
- **Type**: Embedded key-value store
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- Built-in replication and sharding
- More complex deployment
### Neo4j Backend (next-orly-neo4j)
- **Type**: Native graph database
- **Architecture**: Client-server with Neo4j Community Edition
- **Best for**: Graph queries, relationship-heavy workloads, social network analysis
- **Characteristics**:
- Optimized for relationship traversal (e.g., follow graphs, event references)
- Native Cypher query language for graph patterns
- ACID transactions with graph-native storage
- Network overhead from Bolt protocol
- Excellent for complex graph queries (finding common connections, recommendation systems)
- Higher memory usage for graph indexes
- Ideal for analytics and social graph exploration
### Comparing the Backends
The benchmark results will show:
- **Latency differences**: Embedded vs. distributed overhead
- **Throughput trade-offs**: Single-process optimization vs. distributed scalability
- **Latency differences**: Embedded vs. distributed overhead, graph traversal efficiency
- **Throughput trade-offs**: Single-process optimization vs. distributed scalability vs. graph query optimization
- **Resource usage**: Memory and CPU patterns for different architectures
- **Query performance**: Graph queries (Neo4j) vs. key-value lookups (Badger) vs. distributed queries (DGraph)
This comparison helps determine which backend is appropriate for different deployment scenarios.
This comparison helps determine which backend is appropriate for different deployment scenarios and workload patterns.
## Benchmark Results Interpretation