Apache Pulsar vs Celery: Distributed Task Queue

Struggling to choose between Apache Pulsar and Celery: Distributed Task Queue? Both products offer unique advantages, making it a tough decision.

Apache Pulsar is a Development solution with tags like pubsub, messaging, distributed-systems, low-latency, durable-storage.

It boasts features such as Multi-tenancy, Geo-replication, Automatic data partitioning, Tiered storage, Low publish latency, Guaranteed message delivery, Multiple subscription modes and pros including High throughput, Low latency, Durable message storage, Flexible scalability, Multiple subscription modes.

On the other hand, Celery: Distributed Task Queue is a Development product tagged with python, asynchronous, task-queue, job-queue, distributed.

Its standout features include Distributed - Celery is designed to run on multiple nodes, Async task queue - Allows defining, running and monitoring async tasks, Scheduling - Supports scheduling tasks to run at specific times, Integration - Integrates with many services like Redis, RabbitMQ, SQLAlchemy, Django, etc., and it shines with pros like Reliability - Tasks run distributed across nodes provides fault tolerance, Flexibility - Many configuration options to tune and optimize, Active community - Well maintained and good documentation.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Apache Pulsar

Apache Pulsar

Apache Pulsar is an open-source distributed pub-sub messaging system originally created by Yahoo and now under the Apache Software Foundation. It is horizontally scalable, provides low latency and durable storage for messages.

Categories:
pubsub messaging distributed-systems low-latency durable-storage

Apache Pulsar Features

  1. Multi-tenancy
  2. Geo-replication
  3. Automatic data partitioning
  4. Tiered storage
  5. Low publish latency
  6. Guaranteed message delivery
  7. Multiple subscription modes

Pricing

  • Open Source

Pros

High throughput

Low latency

Durable message storage

Flexible scalability

Multiple subscription modes

Cons

Complex configuration

Steep learning curve

No built-in security features

Limited monitoring and management tools


Celery: Distributed Task Queue

Celery: Distributed Task Queue

Celery is an open source Python library for handling asynchronous tasks and job queues. It allows defining tasks that can be executed asynchronously, monitoring them, and getting notified when they are finished. Celery supports scheduling tasks and integrating with a variety of services.

Categories:
python asynchronous task-queue job-queue distributed

Celery: Distributed Task Queue Features

  1. Distributed - Celery is designed to run on multiple nodes
  2. Async task queue - Allows defining, running and monitoring async tasks
  3. Scheduling - Supports scheduling tasks to run at specific times
  4. Integration - Integrates with many services like Redis, RabbitMQ, SQLAlchemy, Django, etc.

Pricing

  • Open Source

Pros

Reliability - Tasks run distributed across nodes provides fault tolerance

Flexibility - Many configuration options to tune and optimize

Active community - Well maintained and good documentation

Cons

Complexity - Can have a steep learning curve

Overhead - Running a distributed system has overhead

Versioning - Upgrading Celery and dependencies can cause issues