# 📨 Messaging and streaming platforms

## Platform overview

| Platform | Type | Language | Protocol | Persistence | Use case |
|-----------|-----|-------|----------|-------------|----------|
| **Apache Kafka** | Distributed event store | Java/Scala | Binary (TCP) | Disk (log) | Event streaming, data pipeline, log aggregation |
| **RabbitMQ** | Message broker | Erlang | AMQP 0-9-1, MQTT, STOMP | Disk / RAM | Application messaging, task queue, RPC |
| **Apache Pulsar** | Distributed messaging + streaming | Java | Binary (TCP) + REST | Disk (segmented log) | Streaming + queue in one, multi-tenant |
| **NATS** | Lightweight messaging | Go | NATS protocol (TCP) | Memory / JetStream (disk) | Microservices, IoT, edge, low-latency |
| **AWS SQS** | Managed queue | — | HTTPS | Managed | Decoupling services, serverless |
| **AWS SNS** | Managed pub/sub | — | HTTPS, SQS, Lambda, email | Managed | Push notifications, fanout |
| **Azure Service Bus** | Managed messaging | — | AMQP, HTTPS | Managed | Enterprise messaging, sessions, transactions |
| **Google Pub/Sub** | Managed streaming | — | gRPC, REST | Managed | Event-driven, data pipeline |
| **Red Hat AMQ 7** (Artemis) | Message broker | Java | AMQP, MQTT, STOMP, OpenWire | Disk | Enterprise, JMS, high-availability |
| **Oracle Service Bus (OSB)** | Enterprise ESB | Java | HTTP/S, JMS, SOAP, REST, MQ, FTP, AQ | Managed (WebLogic) | Enterprise integration, SOA, protocol mediation, routing |

---

## Platform details

### Apache Kafka

**Architecture:**

```
Producer ──► Topic ──► Partition ──► Consumer Group
                │
                ├── Partition 0 (Leader) ──► Broker 1
                ├── Partition 1 (Follower) ──► Broker 2
                └── Partition 2 (Follower) ──► Broker 3
```

| Concept | Description |
|---------|-------|
| **Topic** | Logical message category |
| **Partition** | Append-only log, ordered sequence of messages |
| **Broker** | Server in Kafka cluster |
| **Producer** | Publishes messages to topic |
| **Consumer** | Reads messages from partition (within consumer group) |
| **Consumer Group** | Group of consumers sharing topic reading |
| **Offset** | Position in partition (tracked by consumer) |
| **KRaft** | Controller quorum (replaces Zookeeper from Kafka 3.x) |

**Replication and HA:**

| Parameter | Value |
|----------|---------|
| Replication factor | 2–3 (typically 3 for production) |
| ISR (In-Sync Replicas) | Number of replicas keeping up with leader |
| Min ISR | Minimum ISR for acknowledging writes (acks=all) |
| acks=0 | Fire-and-forget (fastest, possible data loss) |
| acks=1 | Write acknowledged by leader (compromise) |
| acks=all | Write acknowledged by all ISR (safest) |
| Leader failover | Automatic election of new leader from ISR |

**Important configuration:**

```properties
# Production
replication.factor=3
min.insync.replicas=2
default.replication.factor=3

# Retention
log.retention.hours=168     # 7 days
log.retention.bytes=-1      # unlimited (or limit)
log.segment.bytes=1073741824 # 1 GB per segment

# Performance
num.partitions=3            # adjust per need (scale-out)
compression.type=snappy     # (snappy, gzip, lz4, zstd)
```

**Partitioning strategies:**

| Strategy | Key | Advantage | Disadvantage |
|----------|------|--------|----------|
| Round-robin | null | Even distribution | Per-key ordering lost |
| Key-based | user_id, order_id | Same key → same partition | Uneven distribution (hot keys) |
| Custom partitioner | Custom logic | Per use-case optimization | More complex maintenance |

### RabbitMQ

**Architecture:**

```
Producer ──► Exchange ──► Binding ──► Queue ──► Consumer
                  │
      ┌───────────┼───────────┐
      ▼           ▼           ▼
  Direct      Topic      Fanout
  Exchange   Exchange   Exchange
```

| Concept | Description |
|---------|-------|
| **Exchange** | Receives messages from producer, routes to queue |
| **Binding** | Exchange → queue link with routing key |
| **Queue** | FIFO message queue (consumed by consumer) |
| **Virtual Host (vhost)** | Tenant isolation within a single cluster |
| **Publisher Confirm** | Broker acknowledges message receipt |
| **Consumer Ack** | Consumer acknowledges message processing |

**Exchange types:**

| Type | Routing | Use case |
|-----|---------|----------|
| **Direct** | routing_key = binding_key | Task queue, point-to-point |
| **Topic** | routing_key match binding pattern (wildcard `*`, `#`) | Pub/sub with filtering |
| **Fanout** | All bound queues | Broadcast, event notification |
| **Headers** | AMQP headers match | Complex routing (not routing key dependent) |

**Queue types:**

```properties
# Classic Queue (deprecated in production)
x-queue-type: classic

# Quorum Queue (recommended for production)
x-queue-type: quorum
x-quorum-initial-group-size: 3
x-dead-letter-exchange: dlx

# Stream Queue (for large backlogs)
x-queue-type: stream
x-max-length-bytes: 1073741824
```

**HA and clustering:**

| Mode | Description | Use case |
|-------|-------|----------|
| **Quorum Queues** | Raft-based replication (3–5 node), auto failover | Production, HA messaging |
| **Federation** | Async message forwarding between independent RabbitMQ clusters | Multi-region, DR |
| **Shovel** | Point-to-point message forwarding (Federation at queue level) | Migration, specific routing |
| **Warm Standby (DR)** | Secondary cluster, started on failover | Cold DR |

### Apache Pulsar

**Unique architecture (compute/storage separation):**

```
┌──────────────┐    ┌──────────────┐    ┌──────────────┐
│  Producer    │    │  Consumer    │    │  Consumer    │
└──────┬───────┘    └──────┬───────┘    └──────┬───────┘
       │                   │                   │
┌──────▼───────────────────▼───────────────────▼──────┐
│               Broker (stateless)                    │
│         Subscription: Exclusive / Shared / Failover │
└──────────────────────┬──────────────────────────────┘
                       │
┌──────────────────────▼──────────────────────────────┐
│           BookKeeper (stateful storage)              │
│  ├── Bookie 1  ├── Bookie 2  ├── Bookie 3  ├── ... │
│  └── Ledger (append-only, segmented log)            │
└─────────────────────────────────────────────────────┘
```

| Concept | Description |
|---------|-------|
| **Topic** | Logical category (partitioned or non-partitioned) |
| **Subscription** | Delivery mode (Exclusive, Shared, Failover, Key_Shared) |
| **Ledger** | Storage unit in BookKeeper (append-only) |
| **Bookie** | Storage node (BookKeeper) |
| **Managed Ledger** | Segmented log with cache and retention |

**Advantages over Kafka:**
- Compute/storage separation — independent scaling
- Geo-replication built-in (native)
- Multi-tenant (namespaces, isolation)
- TTL, retry, dead letter topic (built-in)
- Read-at-least-once / effectively-once

### NATS

| Feature | Description |
|---------|-------|
| **Core NATS** | Pub/sub, request-reply, < 1 ms latency |
| **JetStream** | Persistence, exactly-once, key-value store, object store |
| **Leaf nodes** | Hierarchical cluster connection |
| **Super-cluster** | Multi-region clustering (global) |

**Use case:** IoT, edge computing, microservices communication, low-latency messaging.

### Oracle Service Bus (OSB)

Part of Oracle SOA Suite, runs on WebLogic Server. Enterprise service bus for integration in Oracle-heavy environments.

| Concept | Description |
|---------|-------|
| **Proxy Service** | Inbound endpoint (HTTP, JMS, MQ, SOAP, REST) |
| **Business Service** | Target backend service |
| **Pipeline** | Message processing — routing, transformation, validation |
| **Split-Join** | Parallel/sequential orchestration of multiple services |
| **Reporting** | Message tracking, SLA monitoring |

**Key features:**
- **Protocol mediation** — translation between SOAP/REST/JMS/MQ/FTP
- **Message transformation** — XSLT, XQuery, MFL (non-XML)
- **Throttling, SLA, alerting** — built-in
- **Oracle AQ (Advanced Queuing)** — integration with Oracle DB queues
- **XPath, XQuery, XSLT 2.0/3.0** — native support
- **Error handling** — fault policies, error queues, retry

**Use case:** Enterprise SOA, Oracle DB → Kafka bridging, legacy mainframe wrapping, B2B integration.

**Alternatives:** IBM Integration Bus (IIB), MuleSoft Anypoint, WSO2 EI, Apache Camel / ServiceMix.

---

## Platform comparison

### Performance and scaling

| Platform | Max throughput | Latency (P99) | Messages/s (1 broker) | Scaling |
|-----------|--------------|---------------|-------------------------|-----------|
| **Kafka** | > 1 GB/s | 2–10 ms | ~1,000,000 | Partitions (horizontal) |
| **Pulsar** | > 1 GB/s | 5–15 ms | ~1,000,000 | Brokers + Bookies |
| **RabbitMQ** | ~100 MB/s | < 1 ms (RAM) | ~100,000 | Clustering (node) |
| **NATS** | > 10 GB/s | < 0.5 ms | ~10,000,000 | Clustering + Leaf nodes |
| **OSB** | < 1 GB/s | 10–100 ms | ~10,000 | Vertical (WebLogic cluster)

### Delivery guarantees

| Platform | At most once | At least once | Exactly once | Ordering |
|-----------|-------------|---------------|-------------|----------|
| **Kafka** | Yes | Yes (acks=all + min.insync) | Yes (idempotent + transactional) | Per partition |
| **Pulsar** | Yes | Yes | Yes (dedup + transactional) | Per partition |
| **RabbitMQ** | Yes | Yes (Publisher Confirm + Consumer Ack) | Limited | Per queue |
| **NATS** | Yes | Yes (JetStream) | Limited | Per subject |
| **OSB** | Yes | Yes (XA transactions, exactly-once delivery) | Yes (XA + WS-AT) | Per pipeline |

### When to use what

| Use case | Recommended platform | Reasoning |
|----------|---------------------|------------|
| **Event sourcing / audit log** | Kafka, Pulsar | Append-only log, high throughput, replay |
| **CDC (Change Data Capture)** | Kafka (Kafka Connect + Debezium) | Connector ecosystem |
| **Task queue (job processing)** | RabbitMQ, SQS | Dead letter, retry, priority, scheduling |
| **API messaging / microservices** | NATS, RabbitMQ | Low latency, simplicity |
| **Data pipeline (ETL)** | Kafka (KSQL, Kafka Streams) | Stream processing in platform |
| **IoT / Edge** | NATS, MQTT (RabbitMQ) | Lightweight, leaf nodes |
| **Enterprise SOA / EAI** | OSB, IBM IIB, MuleSoft | Protocol mediation, XA, B2B, legacy wrapping |
| **Multi-tenant cloud** | Pulsar | Native multi-tenant, geo-replication |
| **Serverless / event-driven** | SQS/SNS, Pub/Sub | Managed, auto-scaling |

---

## DR and high availability

See [DATACENTERS.en.md](DATACENTERS.en.md) — section "Impact of individual technologies on DC topology selection" for detailed DR mapping per platform.

### Best practices

- **Don't lose messages in queue** — prefer acknowledgement-based consumption (not auto-ack)
- **Dead letter queue** — every main queue has a DLQ for undeliverable messages
- **Monitor lag** — consumer lag is a key metric (Kafka: `kafka.consumer:consumer_lag`)
- **Idempotent consumer** — same message may be delivered twice
- **Retry with backoff** — exponential backoff on processing failure
- **Schema registry** — avoid deserialization errors (Avro, Protobuf, JSON Schema)
- **Encryption** — TLS in transit, encryption at rest (Kafka: cluster-side + topic-level)

---

## Related

- [DATACENTERS.en.md](DATACENTERS.en.md) — DR topology, per-platform mapping
- [CLOUD.en.md](CLOUD.en.md) — managed messaging (SQS, SNS, Service Bus, Pub/Sub)

## Sources

Links, books, and standards: [sources/infrastructure/sources.en.md](sources/infrastructure/sources.en.md)

*Last revision: 2026-06-12*