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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. Dramatiq vs Starling

Dramatiq vs Starling

OverviewComparisonAlternatives

Overview

Starling
Starling
Stacks8
Followers11
Votes0
GitHub Stars463
Forks59
Dramatiq
Dramatiq
Stacks6
Followers35
Votes0

Dramatiq vs Starling: What are the differences?

# Introduction
Dramatiq and Starling are two popular tools used for task processing and job queues in Python applications. Both offer features to handle background tasks efficiently.

1. **Concurrency Model**: Dramatiq uses event-driven concurrency based on asyncio where each task is handled by an actor process asynchronously, while Starling uses a more traditional thread-based model where each task runs in parallel within a pool of worker threads.

2. **Transport Protocol**: Dramatiq supports multiple transport protocols such as AMQP, Redis, and more, providing flexibility in choosing how tasks are distributed and processed. In contrast, Starling primarily relies on Redis as the messaging broker, simplifying the setup but offering less protocol variety.

3. **Extensibility**: Dramatiq comes with a robust plugin system allowing developers to extend functionality easily by adding custom middleware or custom message serialization, providing a high level of customization. Starling, on the other hand, has a simpler architecture without as many extension points, limiting the level of customization available.

4. **Monitoring and Metrics**: Dramatiq offers built-in metrics tracking and monitoring tools, making it easier to analyze task performance and monitor queue health. Starling lacks such built-in monitoring features, requiring developers to implement external tools for tracking metrics and monitoring queue performance.

5. **Community Support**: Dramatiq has a strong and active community that regularly contributes updates and new features, ensuring ongoing support and development. While Starling also has community support, it may not be as extensive or active as Dramatiq's community, potentially leading to slower updates and fewer resources available for assistance.

6. **Documentation**: Dramatiq is well-documented with comprehensive guides and examples, making it easier for developers to get started and troubleshoot issues. In comparison, Starling's documentation may be more limited or lacking in detailed explanations, potentially causing challenges for users looking to leverage advanced features or solve complex problems.

In Summary, Dramatiq and Starling differ significantly in their concurrency models, transport protocols, extensibility, monitoring capabilities, community support, and documentation quality, making each tool suitable for different use cases and development preferences.

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Detailed Comparison

Starling
Starling
Dramatiq
Dramatiq

Starling is a powerful but simple messaging server that enables reliable distributed queuing with an absolutely minimal overhead. It speaks the MemCache protocol for maximum cross-platform compatibility. Any language that speaks MemCache can take advantage of Starling's queue facilities.

A distributed task queueing library that is simple and has sane defaults for most SaaS workloads. It draws inspiration from GAE Push Queues and Sidekiq.

Written by Blaine Cook at Twitter;Starling is a Message Queue Server based on MemCached;Written in Ruby;Stores jobs in memory (message queue)
high reliability; simple and easy to understand core; convention over configuration
Statistics
GitHub Stars
463
GitHub Stars
-
GitHub Forks
59
GitHub Forks
-
Stacks
8
Stacks
6
Followers
11
Followers
35
Votes
0
Votes
0

What are some alternatives to Starling, Dramatiq?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

Amazon SQS

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Gearman

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

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