# Go vs .NET NATS Server — Benchmark Comparison

Benchmark run: 2026-03-13 11:41 AM America/Indiana/Indianapolis. Both servers ran on the same machine using the benchmark project README command (`dotnet test tests/NATS.Server.Benchmark.Tests --filter "Category=Benchmark" -v normal --logger "console;verbosity=detailed"`). Test parallelization remained disabled inside the benchmark assembly.

**Environment:** Apple M4, .NET SDK 10.0.101, benchmark README command run in the benchmark project's default `Debug` configuration, Go toolchain installed, Go reference server built from `golang/nats-server/`.

---
---

## Core NATS — Pub/Sub Throughput

### Single Publisher (no subscribers)

| Payload | Go msg/s | Go MB/s | .NET msg/s | .NET MB/s | Ratio (.NET/Go) |
|---------|----------|---------|------------|-----------|-----------------|
| 16 B | 2,223,690 | 33.9 | 1,341,067 | 20.5 | 0.60x |
| 128 B | 2,218,308 | 270.8 | 1,577,523 | 192.6 | 0.71x |

### Publisher + Subscriber (1:1)

| Payload | Go msg/s | Go MB/s | .NET msg/s | .NET MB/s | Ratio (.NET/Go) |
|---------|----------|---------|------------|-----------|-----------------|
| 16 B | 292,711 | 4.5 | 862,381 | 13.2 | **2.95x** |
| 16 KB | 32,890 | 513.9 | 28,906 | 451.7 | 0.88x |

### Fan-Out (1 Publisher : 4 Subscribers)

| Payload | Go msg/s | Go MB/s | .NET msg/s | .NET MB/s | Ratio (.NET/Go) |
|---------|----------|---------|------------|-----------|-----------------|
| 128 B | 2,945,790 | 359.6 | 1,858,235 | 226.8 | 0.63x |

### Multi-Publisher / Multi-Subscriber (4P x 4S)

| Payload | Go msg/s | Go MB/s | .NET msg/s | .NET MB/s | Ratio (.NET/Go) |
|---------|----------|---------|------------|-----------|-----------------|
| 128 B | 2,123,480 | 259.2 | 1,392,249 | 170.0 | 0.66x |

---

## Core NATS — Request/Reply Latency

### Single Client, Single Service

| Payload | Go msg/s | .NET msg/s | Ratio | Go P50 (us) | .NET P50 (us) | Go P99 (us) | .NET P99 (us) |
|---------|----------|------------|-------|-------------|---------------|-------------|---------------|
| 128 B | 8,386 | 7,014 | 0.84x | 115.8 | 139.0 | 175.5 | 193.0 |

### 10 Clients, 2 Services (Queue Group)

| Payload | Go msg/s | .NET msg/s | Ratio | Go P50 (us) | .NET P50 (us) | Go P99 (us) | .NET P99 (us) |
|---------|----------|------------|-------|-------------|---------------|-------------|---------------|
| 16 B | 26,470 | 23,478 | 0.89x | 370.2 | 410.6 | 486.0 | 592.8 |

---

## JetStream — Publication

| Mode | Payload | Storage | Go msg/s | .NET msg/s | Ratio (.NET/Go) |
|------|---------|---------|----------|------------|-----------------|
| Synchronous | 16 B | Memory | 14,812 | 12,134 | 0.82x |
| Async (batch) | 128 B | File | 148,156 | 57,479 | 0.39x |

> **Note:** Async file-store publish remains well below parity at 0.39x, but it is still materially better than the older 0.30x snapshot that motivated this FileStore round.

---

## JetStream — Consumption

| Mode | Go msg/s | .NET msg/s | Ratio (.NET/Go) |
|------|----------|------------|-----------------|
| Ordered ephemeral consumer | 572,941 | 101,944 | 0.18x |
| Durable consumer fetch | 599,204 | 338,265 | 0.56x |

> **Note:** Ordered-consumer throughput remains the clearest JetStream hotspot after this round. The merged FileStore work helped publish and subject-lookup paths more than consumer delivery.

---

## Hot Path Microbenchmarks (.NET only)

### SubList

| Benchmark | .NET msg/s | .NET MB/s | Alloc |
|-----------|------------|-----------|-------|
| SubList Exact Match (128 subjects) | 16,497,186 | 220.3 | 0.00 B/op |
| SubList Wildcard Match | 16,147,367 | 215.6 | 0.00 B/op |
| SubList Queue Match | 15,582,052 | 118.9 | 0.00 B/op |
| SubList Remote Interest | 259,940 | 4.2 | 0.00 B/op |

### Parser

| Benchmark | Ops/s | MB/s | Alloc |
|-----------|-------|------|-------|
| Parser PING | 6,283,578 | 36.0 | 0.0 B/op |
| Parser PUB | 2,712,550 | 103.5 | 40.0 B/op |
| Parser HPUB | 2,338,555 | 124.9 | 40.0 B/op |
| Parser PUB split payload | 2,043,813 | 78.0 | 176.0 B/op |

### FileStore

| Benchmark | Ops/s | MB/s | Alloc |
|-----------|-------|------|-------|
| FileStore AppendAsync (128B) | 244,089 | 29.8 | 1552.9 B/op |
| FileStore LoadLastBySubject (hot) | 12,784,127 | 780.3 | 0.0 B/op |
| FileStore PurgeEx+Trim | 332 | 0.0 | 5440792.9 B/op |

---

## Summary

| Category | Ratio Range | Assessment |
|----------|-------------|------------|
| Pub-only throughput | 0.60x–0.71x | Mixed; still behind Go |
| Pub/sub (small payload) | **2.95x** | .NET outperforms Go decisively |
| Pub/sub (large payload) | 0.88x | Close, but below parity |
| Fan-out | 0.63x | Still materially behind Go |
| Multi pub/sub | 0.66x | Meaningful gap remains |
| Request/reply latency | 0.84x–0.89x | Good |
| JetStream sync publish | 0.82x | Strong |
| JetStream async file publish | 0.39x | Improved versus older snapshots, still storage-bound |
| JetStream ordered consume | 0.18x | Highest-priority JetStream gap |
| JetStream durable fetch | 0.56x | Regressed from prior snapshot |

### Key Observations

1. **Small-payload 1:1 pub/sub is back to a large `.NET` lead in this final run** at 2.95x (862K vs 293K msg/s). That puts the merged benchmark profile much closer to the earlier comparison snapshot than the intermediate integration-only run.
2. **Async file-store publish is still materially better than the older 0.30x baseline** at 0.39x (57.5K vs 148.2K msg/s), which is consistent with the FileStore metadata and payload-ownership changes helping the write path even though they did not eliminate the gap.
3. **The new FileStore direct benchmarks show what remains expensive in storage maintenance**: `LoadLastBySubject` is allocation-free and extremely fast, `AppendAsync` is still about 1553 B/op, and repeated `PurgeEx+Trim` still burns roughly 5.4 MB/op.
4. **Ordered consumer throughput remains the largest JetStream gap at 0.18x** (102K vs 573K msg/s). That is better than the intermediate 0.11x run, but it is still the clearest post-FileStore optimization target.
5. **Durable fetch regressed to 0.56x in the final run**, which keeps consumer delivery and storage-read coordination in the top tier of remaining work even after the FileStore changes.
6. **Parser and SubList microbenchmarks remain stable and low-allocation**. The storage and consumer layers continue to dominate the server-level benchmark gaps, not the parser or subject matcher hot paths.

---

## Optimization History

### Round 6: Batch Flush Signaling + Fetch Optimizations

Four optimizations targeting fan-out and consumer fetch hot paths:

| # | Root Cause | Fix | Impact |
|---|-----------|-----|--------|
| 20 | **Per-subscriber flush signal in fan-out** — each `SendMessage` called `_flushSignal.Writer.TryWrite(0)` independently; for 1:4 fan-out, 4 channel writes + 4 write-loop wakeups per published message | Split `SendMessage` into `SendMessageNoFlush` + `SignalFlush`; `ProcessMessage` collects unique clients in `[ThreadStatic] HashSet<INatsClient>` (Go's `pcd` pattern), one flush signal per unique client after fan-out | Reduces channel writes from N to unique-client-count per publish |
| 21 | **Per-fetch `CompiledFilter` allocation** — `CompiledFilter.FromConfig(consumer.Config)` called on every fetch request, allocating a new filter object each time | Cached `CompiledFilter` on `ConsumerHandle` with staleness detection (reference + value check on filter config fields); reused across fetches | Eliminates per-fetch filter allocation |
| 22 | **Per-message string interpolation in ack reply** — `$"$JS.ACK.{stream}.{consumer}.1.{seq}.{deliverySeq}.{ts}.{pending}"` allocated intermediate strings and boxed numeric types on every delivery | Pre-compute `$"$JS.ACK.{stream}.{consumer}.1."` prefix before loop; use `stackalloc char[]` + `TryFormat` for numeric suffix — zero intermediate allocations | Eliminates 4+ string allocs per delivered message |
| 23 | **Per-fetch `List<StoredMessage>` allocation** — `new List<StoredMessage>(batch)` allocated on every `FetchAsync` call | `[ThreadStatic]` reusable list with `.Clear()` + capacity growth; `PullFetchBatch` snapshots via `.ToArray()` for safe handoff | Eliminates per-fetch list allocation |

### Round 5: Non-blocking ConsumeAsync (ordered + durable consumers)

One root cause was identified and fixed in the MSG.NEXT request handling path:

| # | Root Cause | Fix | Impact |
|---|-----------|-----|--------|
| 19 | **Synchronous blocking in DeliverPullFetchMessages** — `FetchAsync(...).GetAwaiter().GetResult()` blocked the client's read loop for the full `expires` timeout (30s). With `batch=1000` and only 5 messages available, the fetch polled for message 6 indefinitely. No messages were delivered until the timeout fired, causing the client to receive 0 messages before its own timeout. | Split into two paths: `noWait`/no-expires uses synchronous fetch (existing behavior for `FetchAsync` client); `expires > 0` spawns `DeliverPullFetchMessagesAsync` background task that delivers messages incrementally without blocking the read loop, with idle heartbeat support | Enables `ConsumeAsync` for both ordered and durable consumers; ordered consumer: 99K msg/s (0.64x Go) |

### Round 4: Per-Client Direct Write Buffer (pub/sub + fan-out + multi pub/sub)

Four optimizations were implemented in the message delivery hot path:

| # | Root Cause | Fix | Impact |
|---|-----------|-----|--------|
| 15 | **Per-message channel overhead** — each `SendMessage` call went through `Channel<OutboundData>.TryWrite`, incurring lock contention and memory barriers | Replaced channel-based message delivery with per-client `_directBuf` byte array under `SpinLock`; messages written directly to contiguous buffer | Eliminates channel overhead per delivery |
| 16 | **Per-message heap allocation for MSG header** — `_outboundBufferPool.RentBuffer()` allocated a pooled `byte[]` for each MSG header | Replaced with `stackalloc byte[512]` — MSG header formatted entirely on the stack, then copied into `_directBuf` | Zero heap allocations per delivery |
| 17 | **Per-message socket write** — write loop issued one `SendAsync` per channel item, even with coalescing | Double-buffer swap: write loop swaps `_directBuf` ↔ `_writeBuf` under `SpinLock`, then writes the entire batch in a single `SendAsync`; zero allocation on swap | Single syscall per batch, zero-copy buffer reuse |
| 18 | **Separate wake channels** — `SendMessage` and `WriteProtocol` used different signaling paths | Unified on `_flushSignal` channel (bounded capacity 1, DropWrite); both paths signal the same channel, write loop drains both `_directBuf` and `_outbound` on each wake | Single wait point, no missed wakes |

### Round 3: Outbound Write Path (pub/sub + fan-out + fetch)

Three root causes were identified and fixed in the message delivery hot path:

| # | Root Cause | Fix | Impact |
|---|-----------|-----|--------|
| 12 | **Per-message `.ToArray()` allocation in SendMessage** — `owner.Memory[..pos].ToArray()` created a new `byte[]` for every MSG delivered to every subscriber | Replaced `IMemoryOwner` rent/copy/dispose with direct `byte[]` from pool; write loop returns buffers after writing | Eliminates 1 heap alloc per delivery (4 per fan-out message) |
| 13 | **Per-message `WriteAsync` in write loop** — each queued message triggered a separate `_stream.WriteAsync()` system call | Added 64KB coalesce buffer; drain all pending messages into contiguous buffer, single `WriteAsync` per batch | Reduces syscalls from N to 1 per batch |
| 14 | **Profiling `Stopwatch` on every message** — `Stopwatch.StartNew()` ran unconditionally in `ProcessMessage` and `StreamManager.Capture` even for non-JetStream messages | Removed profiling instrumentation from hot path | Eliminates ~200ns overhead per message |

### Round 2: FileStore AppendAsync Hot Path

| # | Root Cause | Fix | Impact |
|---|-----------|-----|--------|
| 6 | **Async state machine overhead** — `AppendAsync` was `async ValueTask<ulong>` but never actually awaited | Changed to synchronous `ValueTask<ulong>` returning `ValueTask.FromResult(_last)` | Eliminates Task state machine allocation |
| 7 | **Double payload copy** — `TransformForPersist` allocated `byte[]` then `payload.ToArray()` created second copy for `StoredMessage` | Reuse `TransformForPersist` result directly for `StoredMessage.Payload` when no transform needed (`_noTransform` flag) | Eliminates 1 `byte[]` alloc per message |
| 8 | **Unnecessary TTL work per publish** — `ExpireFromWheel()` and `RegisterTtl()` called on every write even when `MaxAge=0` | Guarded both with `_options.MaxAgeMs > 0` check (matches Go: `filestore.go:4701`) | Eliminates hash wheel overhead when TTL not configured |
| 9 | **Per-message MsgBlock cache allocation** — `WriteAt` created `new MessageRecord` for `_cache` on every write | Removed eager cache population; reads now decode from pending buffer or disk | Eliminates 1 object alloc per message |
| 10 | **Contiguous write buffer** — `MsgBlock._pendingWrites` was `List<byte[]>` with per-message `byte[]` allocations | Replaced with single contiguous `_pendingBuf` byte array; `MessageRecord.EncodeTo` writes directly into it | Eliminates per-message `byte[]` encoding alloc; single `RandomAccess.Write` per flush |
| 11 | **Pending buffer read path** — `MsgBlock.Read()` flushed pending writes to disk before reading | Added in-memory read from `_pendingBuf` when data is still in the buffer | Avoids unnecessary disk flush on read-after-write |

### Round 1: FileStore/StreamManager Layer

| # | Root Cause | Fix | Impact |
|---|-----------|-----|--------|
| 1 | **Per-message synchronous disk I/O** — `MsgBlock.WriteAt()` called `RandomAccess.Write()` on every message | Added write buffering in MsgBlock + background flush loop in FileStore (Go's `flushLoop` pattern: coalesce 16KB or 8ms) | Eliminates per-message syscall overhead |
| 2 | **O(n) `GetStateAsync` per publish** — `_messages.Keys.Min()` and `_messages.Values.Sum()` on every publish for MaxMsgs/MaxBytes checks | Added incremental `_messageCount`, `_totalBytes`, `_firstSeq` fields updated in all mutation paths; `GetStateAsync` is now O(1) | Eliminates O(n) scan per publish |
| 3 | **Unnecessary `LoadAsync` after every append** — `StreamManager.Capture` reloaded the just-stored message even when no mirrors/sources were configured | Made `LoadAsync` conditional on mirror/source replication being configured | Eliminates redundant disk read per publish |
| 4 | **Redundant `PruneExpiredMessages` per publish** — called before every publish even when `MaxAge=0`, and again inside `EnforceRuntimePolicies` | Guarded with `MaxAgeMs > 0` check; removed the pre-publish call (background expiry timer handles it) | Eliminates O(n) scan per publish |
| 5 | **`PrunePerSubject` loading all messages per publish** — `EnforceRuntimePolicies` → `PrugePerSubject` called `ListAsync().GroupBy()` even when `MaxMsgsPer=0` | Guarded with `MaxMsgsPer > 0` check | Eliminates O(n) scan per publish |

Additional fixes: SHA256 envelope bypass for unencrypted/uncompressed stores, RAFT propose skip for single-replica streams.

### What would further close the gap

| Change | Expected Impact | Go Reference |
|--------|----------------|-------------|
| **Fan-out parallelism** | Deliver to subscribers concurrently instead of serially from publisher's read loop | Go: `processMsgResults` fans out per-client via goroutines |
| **Eliminate per-message GC allocations in FileStore** | ~30% improvement on FileStore AppendAsync — replace `StoredMessage` class with `StoredMessageMeta` struct in `_messages` dict, reconstruct full message from MsgBlock on read | Go stores in `cache.buf`/`cache.idx` with zero per-message allocs; 80+ sites in FileStore.cs need migration |
| **Ordered consumer delivery optimization** | Investigate .NET ordered consumer throughput ceiling (~110K msg/s) vs Go's variable 156K–749K | Go: consumer.go ordered consumer fast path |
