Redis to RabbitMQ: Unveiling the Reasons Behind the Broker Switch

Ashwani Paliwal
November 25, 2023

In the intricate world of task queue management within projects, the choice of message broker can significantly impact performance, reliability, and scalability. Redis, with its speed and simplicity, had been a go-to choice for many, including us, until we found ourselves encountering recurrent issues that impeded our workflow and task handling. This led to a pivotal decision to transition from Redis to RabbitMQ as our message broker. In this blog post, we'll delve into the reasons behind this switch and the advantages RabbitMQ brought to our workflow.

Redis Limitations and Challenges

Our journey began with Redis serving as the Celery broker, handling the orchestration of tasks within our application. Initially, Redis's simplicity and speed were appealing, especially for handling transient data efficiently. However, as our project grew in complexity and scale, we encountered persistent challenges that hindered our workflow.

Task Redundancy and Visibility Timeout

One of the prominent issues we faced was task redundancy. Redis imposes a visibility timeout period, after which uncompleted tasks are reassigned to other workers. This led to longer tasks being executed repeatedly, causing a cascade effect that stalled other Celery tasks. The one-hour visibility timeout became a bottleneck, hampering our task execution and overall efficiency.

Message Storage Duration

Moreover, Redis's inability to store messages for extended periods posed another challenge. Unlike RabbitMQ, which retains messages until they are acknowledged, Redis's transient nature limited our ability to preserve messages for longer durations.

Queue Mechanism and Complexity Handling

Redis, originally not designed as a message broker but often used as a temporary database, revealed its limitations when confronted with intricate queuing requirements. As our project complexity increased, Redis struggled to manage tasks with proper queuing. This led to Celery instances getting stuck, and a lack of robust queue handling resulted in tasks not being managed effectively.

GitHub Issue: Celery GitHub Issue #4400

Our transition journey stemmed from a critical challenge highlighted in a GitHub issue within the Celery repository. The issue, extensively discussed and experienced by the community, centered around Redis's visibility timeout period causing task redundancy and inefficiency. Longer tasks were repeatedly executed due to Redis reassigning them after the timeout, creating a bottleneck that affected overall task management.

The community's collective experience echoed our own encounters with Redis, exposing its limitations in handling complex task orchestration scenarios. This visibility timeout issue not only affected task execution but also impacted the performance of other Celery tasks, causing delays and inefficiencies within our project workflow.

Transitioning to RabbitMQ

Realizing the constraints posed by Redis in handling our evolving project needs, we made a strategic decision to transition to RabbitMQ. This decision was driven by several compelling reasons:

Tailored Broker Functionality

Unlike Redis, which was not initially designed as a message broker, RabbitMQ is purpose-built for this exact role. Its robust queue mechanism is well-equipped to handle intricate task queuing requirements, providing a more reliable and scalable solution for our project.

Message Retention and Acknowledgment

RabbitMQ's ability to store messages until they are acknowledged perfectly aligned with our need for extended message retention. This feature empowered us to manage tasks more effectively, ensuring messages were preserved until they were successfully processed, eliminating the risk of message loss or reassignment.

Improved Task Tracking and Management

The integration of RabbitMQ's management plugin interface offered unparalleled ease in tracking tasks and managing the queue. This intuitive interface streamlined our workflow, allowing for efficient monitoring and handling of tasks, and enhancing overall project management and visibility.


The decision to transition from Redis to RabbitMQ as our Celery message broker was catalyzed by the growing complexity of our project and the limitations we encountered with Redis. RabbitMQ's tailored functionality, extended message retention, and superior queue management capabilities addressed the challenges we faced, providing a more robust, scalable, and reliable solution for our task queue orchestration needs.

As we continue to evolve our project, the adoption of RabbitMQ has not only resolved our previous issues but also positioned us to handle future complexities with greater efficiency and confidence. The transition underscores the importance of selecting a message broker that aligns with the evolving demands of a project, ensuring seamless task orchestration and streamlined workflow management.

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