275 lines
12 KiB
Markdown
275 lines
12 KiB
Markdown
# 📨 Messaging and streaming platforms
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## Platform overview
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| Platform | Type | Language | Protocol | Persistence | Use case |
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|-----------|-----|-------|----------|-------------|----------|
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| **Apache Kafka** | Distributed event store | Java/Scala | Binary (TCP) | Disk (log) | Event streaming, data pipeline, log aggregation |
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| **RabbitMQ** | Message broker | Erlang | AMQP 0-9-1, MQTT, STOMP | Disk / RAM | Application messaging, task queue, RPC |
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| **Apache Pulsar** | Distributed messaging + streaming | Java | Binary (TCP) + REST | Disk (segmented log) | Streaming + queue in one, multi-tenant |
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| **NATS** | Lightweight messaging | Go | NATS protocol (TCP) | Memory / JetStream (disk) | Microservices, IoT, edge, low-latency |
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| **AWS SQS** | Managed queue | — | HTTPS | Managed | Decoupling services, serverless |
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| **AWS SNS** | Managed pub/sub | — | HTTPS, SQS, Lambda, email | Managed | Push notifications, fanout |
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| **Azure Service Bus** | Managed messaging | — | AMQP, HTTPS | Managed | Enterprise messaging, sessions, transactions |
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| **Google Pub/Sub** | Managed streaming | — | gRPC, REST | Managed | Event-driven, data pipeline |
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| **Red Hat AMQ 7** (Artemis) | Message broker | Java | AMQP, MQTT, STOMP, OpenWire | Disk | Enterprise, JMS, high-availability |
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| **Oracle Service Bus (OSB)** | Enterprise ESB | Java | HTTP/S, JMS, SOAP, REST, MQ, FTP, AQ | Managed (WebLogic) | Enterprise integration, SOA, protocol mediation, routing |
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---
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## Platform details
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### Apache Kafka
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**Architecture:**
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```
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Producer ──► Topic ──► Partition ──► Consumer Group
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│
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├── Partition 0 (Leader) ──► Broker 1
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├── Partition 1 (Follower) ──► Broker 2
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└── Partition 2 (Follower) ──► Broker 3
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```
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| Concept | Description |
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|---------|-------|
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| **Topic** | Logical message category |
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| **Partition** | Append-only log, ordered sequence of messages |
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| **Broker** | Server in Kafka cluster |
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| **Producer** | Publishes messages to topic |
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| **Consumer** | Reads messages from partition (within consumer group) |
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| **Consumer Group** | Group of consumers sharing topic reading |
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| **Offset** | Position in partition (tracked by consumer) |
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| **KRaft** | Controller quorum (replaces Zookeeper from Kafka 3.x) |
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**Replication and HA:**
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| Parameter | Value |
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|----------|---------|
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| Replication factor | 2–3 (typically 3 for production) |
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| ISR (In-Sync Replicas) | Number of replicas keeping up with leader |
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| Min ISR | Minimum ISR for acknowledging writes (acks=all) |
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| acks=0 | Fire-and-forget (fastest, possible data loss) |
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| acks=1 | Write acknowledged by leader (compromise) |
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| acks=all | Write acknowledged by all ISR (safest) |
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| Leader failover | Automatic election of new leader from ISR |
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**Important configuration:**
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```properties
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# Production
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replication.factor=3
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min.insync.replicas=2
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default.replication.factor=3
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# Retention
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log.retention.hours=168 # 7 days
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log.retention.bytes=-1 # unlimited (or limit)
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log.segment.bytes=1073741824 # 1 GB per segment
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# Performance
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num.partitions=3 # adjust per need (scale-out)
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compression.type=snappy # (snappy, gzip, lz4, zstd)
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```
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**Partitioning strategies:**
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| Strategy | Key | Advantage | Disadvantage |
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|----------|------|--------|----------|
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| Round-robin | null | Even distribution | Per-key ordering lost |
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| Key-based | user_id, order_id | Same key → same partition | Uneven distribution (hot keys) |
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| Custom partitioner | Custom logic | Per use-case optimization | More complex maintenance |
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### RabbitMQ
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**Architecture:**
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```
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Producer ──► Exchange ──► Binding ──► Queue ──► Consumer
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│
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┌───────────┼───────────┐
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▼ ▼ ▼
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Direct Topic Fanout
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Exchange Exchange Exchange
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```
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| Concept | Description |
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|---------|-------|
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| **Exchange** | Receives messages from producer, routes to queue |
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| **Binding** | Exchange → queue link with routing key |
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| **Queue** | FIFO message queue (consumed by consumer) |
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| **Virtual Host (vhost)** | Tenant isolation within a single cluster |
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| **Publisher Confirm** | Broker acknowledges message receipt |
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| **Consumer Ack** | Consumer acknowledges message processing |
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**Exchange types:**
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| Type | Routing | Use case |
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|-----|---------|----------|
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| **Direct** | routing_key = binding_key | Task queue, point-to-point |
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| **Topic** | routing_key match binding pattern (wildcard `*`, `#`) | Pub/sub with filtering |
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| **Fanout** | All bound queues | Broadcast, event notification |
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| **Headers** | AMQP headers match | Complex routing (not routing key dependent) |
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**Queue types:**
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```properties
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# Classic Queue (deprecated in production)
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x-queue-type: classic
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# Quorum Queue (recommended for production)
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x-queue-type: quorum
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x-quorum-initial-group-size: 3
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x-dead-letter-exchange: dlx
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# Stream Queue (for large backlogs)
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x-queue-type: stream
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x-max-length-bytes: 1073741824
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```
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**HA and clustering:**
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| Mode | Description | Use case |
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|-------|-------|----------|
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| **Quorum Queues** | Raft-based replication (3–5 node), auto failover | Production, HA messaging |
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| **Federation** | Async message forwarding between independent RabbitMQ clusters | Multi-region, DR |
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| **Shovel** | Point-to-point message forwarding (Federation at queue level) | Migration, specific routing |
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| **Warm Standby (DR)** | Secondary cluster, started on failover | Cold DR |
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### Apache Pulsar
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**Unique architecture (compute/storage separation):**
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```
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┌──────────────┐ ┌──────────────┐ ┌──────────────┐
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│ Producer │ │ Consumer │ │ Consumer │
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└──────┬───────┘ └──────┬───────┘ └──────┬───────┘
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│ │ │
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┌──────▼───────────────────▼───────────────────▼──────┐
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│ Broker (stateless) │
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│ Subscription: Exclusive / Shared / Failover │
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└──────────────────────┬──────────────────────────────┘
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│
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┌──────────────────────▼──────────────────────────────┐
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│ BookKeeper (stateful storage) │
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│ ├── Bookie 1 ├── Bookie 2 ├── Bookie 3 ├── ... │
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│ └── Ledger (append-only, segmented log) │
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└─────────────────────────────────────────────────────┘
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```
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| Concept | Description |
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|---------|-------|
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| **Topic** | Logical category (partitioned or non-partitioned) |
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| **Subscription** | Delivery mode (Exclusive, Shared, Failover, Key_Shared) |
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| **Ledger** | Storage unit in BookKeeper (append-only) |
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| **Bookie** | Storage node (BookKeeper) |
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| **Managed Ledger** | Segmented log with cache and retention |
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**Advantages over Kafka:**
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- Compute/storage separation — independent scaling
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- Geo-replication built-in (native)
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- Multi-tenant (namespaces, isolation)
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- TTL, retry, dead letter topic (built-in)
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- Read-at-least-once / effectively-once
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### NATS
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| Feature | Description |
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|---------|-------|
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| **Core NATS** | Pub/sub, request-reply, < 1 ms latency |
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| **JetStream** | Persistence, exactly-once, key-value store, object store |
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| **Leaf nodes** | Hierarchical cluster connection |
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| **Super-cluster** | Multi-region clustering (global) |
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**Use case:** IoT, edge computing, microservices communication, low-latency messaging.
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### Oracle Service Bus (OSB)
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Part of Oracle SOA Suite, runs on WebLogic Server. Enterprise service bus for integration in Oracle-heavy environments.
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| Concept | Description |
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|---------|-------|
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| **Proxy Service** | Inbound endpoint (HTTP, JMS, MQ, SOAP, REST) |
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| **Business Service** | Target backend service |
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| **Pipeline** | Message processing — routing, transformation, validation |
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| **Split-Join** | Parallel/sequential orchestration of multiple services |
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| **Reporting** | Message tracking, SLA monitoring |
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**Key features:**
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- **Protocol mediation** — translation between SOAP/REST/JMS/MQ/FTP
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- **Message transformation** — XSLT, XQuery, MFL (non-XML)
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- **Throttling, SLA, alerting** — built-in
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- **Oracle AQ (Advanced Queuing)** — integration with Oracle DB queues
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- **XPath, XQuery, XSLT 2.0/3.0** — native support
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- **Error handling** — fault policies, error queues, retry
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**Use case:** Enterprise SOA, Oracle DB → Kafka bridging, legacy mainframe wrapping, B2B integration.
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**Alternatives:** IBM Integration Bus (IIB), MuleSoft Anypoint, WSO2 EI, Apache Camel / ServiceMix.
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---
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## Platform comparison
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### Performance and scaling
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| Platform | Max throughput | Latency (P99) | Messages/s (1 broker) | Scaling |
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|-----------|--------------|---------------|-------------------------|-----------|
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| **Kafka** | > 1 GB/s | 2–10 ms | ~1,000,000 | Partitions (horizontal) |
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| **Pulsar** | > 1 GB/s | 5–15 ms | ~1,000,000 | Brokers + Bookies |
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| **RabbitMQ** | ~100 MB/s | < 1 ms (RAM) | ~100,000 | Clustering (node) |
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| **NATS** | > 10 GB/s | < 0.5 ms | ~10,000,000 | Clustering + Leaf nodes |
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| **OSB** | < 1 GB/s | 10–100 ms | ~10,000 | Vertical (WebLogic cluster)
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### Delivery guarantees
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| Platform | At most once | At least once | Exactly once | Ordering |
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|-----------|-------------|---------------|-------------|----------|
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| **Kafka** | Yes | Yes (acks=all + min.insync) | Yes (idempotent + transactional) | Per partition |
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| **Pulsar** | Yes | Yes | Yes (dedup + transactional) | Per partition |
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| **RabbitMQ** | Yes | Yes (Publisher Confirm + Consumer Ack) | Limited | Per queue |
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| **NATS** | Yes | Yes (JetStream) | Limited | Per subject |
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| **OSB** | Yes | Yes (XA transactions, exactly-once delivery) | Yes (XA + WS-AT) | Per pipeline |
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### When to use what
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| Use case | Recommended platform | Reasoning |
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|----------|---------------------|------------|
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| **Event sourcing / audit log** | Kafka, Pulsar | Append-only log, high throughput, replay |
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| **CDC (Change Data Capture)** | Kafka (Kafka Connect + Debezium) | Connector ecosystem |
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| **Task queue (job processing)** | RabbitMQ, SQS | Dead letter, retry, priority, scheduling |
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| **API messaging / microservices** | NATS, RabbitMQ | Low latency, simplicity |
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| **Data pipeline (ETL)** | Kafka (KSQL, Kafka Streams) | Stream processing in platform |
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| **IoT / Edge** | NATS, MQTT (RabbitMQ) | Lightweight, leaf nodes |
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| **Enterprise SOA / EAI** | OSB, IBM IIB, MuleSoft | Protocol mediation, XA, B2B, legacy wrapping |
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| **Multi-tenant cloud** | Pulsar | Native multi-tenant, geo-replication |
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| **Serverless / event-driven** | SQS/SNS, Pub/Sub | Managed, auto-scaling |
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---
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## DR and high availability
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See [DATACENTERS.en.md](DATACENTERS.en.md) — section "Impact of individual technologies on DC topology selection" for detailed DR mapping per platform.
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### Best practices
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- **Don't lose messages in queue** — prefer acknowledgement-based consumption (not auto-ack)
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- **Dead letter queue** — every main queue has a DLQ for undeliverable messages
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- **Monitor lag** — consumer lag is a key metric (Kafka: `kafka.consumer:consumer_lag`)
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- **Idempotent consumer** — same message may be delivered twice
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- **Retry with backoff** — exponential backoff on processing failure
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- **Schema registry** — avoid deserialization errors (Avro, Protobuf, JSON Schema)
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- **Encryption** — TLS in transit, encryption at rest (Kafka: cluster-side + topic-level)
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---
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## Related
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- [DATACENTERS.en.md](DATACENTERS.en.md) — DR topology, per-platform mapping
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- [CLOUD.en.md](CLOUD.en.md) — managed messaging (SQS, SNS, Service Bus, Pub/Sub)
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## Sources
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Links, books, and standards: [sources/infrastructure/sources.en.md](sources/infrastructure/sources.en.md)
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*Last revision: 2026-06-12* |