12 KiB
12 KiB
📨 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:
# 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:
# 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 — 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 — DR topology, per-platform mapping
- CLOUD.en.md — managed messaging (SQS, SNS, Service Bus, Pub/Sub)
Sources
Links, books, and standards: sources/infrastructure/sources.md
Last revision: 2026-06-12