# Redis Vs Rabbitmq as a Data Broker/messaging System in Between Logstash and Elasticsearch

When choosing between **Redis** and **RabbitMQ** as a data broker or messaging system between **Logstash** and **Elasticsearch**, it’s important to evaluate based on specific use cases and requirements:

### 1. **Redis**

- **Type**: In-memory data structure store (often used as a message broker, cache, or database).
- **Message Model**: **Pub/Sub** (publish-subscribe) model with no message persistence by default.
- **Throughput**: Extremely high throughput due to its in-memory nature, capable of handling millions of messages per second.
- **Durability**: By default, Redis does not persist messages, but you can configure it with persistence (RDB or AOF) to make it durable.
- **Latency**: Very low latency (microseconds) since it operates primarily in memory.
- **Use Case**: Best suited for real-time, high-throughput scenarios where message persistence is not a key requirement or where data loss is tolerable. For instance, it's ideal for caching or short-lived message queues.
- **Scalability**: Redis can be scaled via clustering, but scaling horizontally can be more complex than RabbitMQ.
- **Complexity**: Simpler setup compared to RabbitMQ; easy to install, configure, and manage.

### 2. **RabbitMQ**

- **Type**: Dedicated message broker (with support for multiple messaging patterns like **Pub/Sub**, **Message Queues**, **Topic**, **Fanout**, etc.).
- **Message Model**: Supports **message queues**, **acknowledgments**, **persistence**, **routing keys**, and complex delivery guarantees.
- **Throughput**: Lower throughput compared to Redis, typically handling around tens to hundreds of thousands of messages per second depending on the setup.
- **Durability**: High durability with message persistence options. Ensures messages are stored on disk and can survive broker failures.
- **Latency**: Higher than Redis but still performant with millisecond-level latency.
- **Use Case**: Ideal when message durability, guaranteed delivery, and complex routing (e.g., fanout, topic exchange) are required. Best for long-lived tasks, processing pipelines, and scenarios where data loss is not acceptable.
- **Scalability**: RabbitMQ can be horizontally scaled via clustering and federation, and it offers flexible routing mechanisms.
- **Complexity**: More complex setup and configuration compared to Redis, with a steeper learning curve due to the advanced messaging features.

### **Recommendation**

- **Redis** would be suitable if:
    - You need extremely high throughput with low latency.
    - Durability is not a major concern (or you can afford to lose some messages).
    - You’re looking for simplicity and lightweight architecture.
- **RabbitMQ** would be better if:
    - You need reliable, durable message delivery with acknowledgments.
    - You have more complex message routing needs or require advanced messaging patterns.
    - You require guaranteed delivery, persistence, and the ability to manage queues more granularly.

For a **Logstash to Elasticsearch** use case, where message delivery, retries, and potential buffering are essential, **RabbitMQ** may be a better fit, ensuring that logs don’t get lost and are delivered in the correct order. **Redis** could be used if you prioritize speed and can afford minor data loss, but it's less common for this specific logging pipeline due to the durability requirements of log systems.