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  1. Stackups
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  3. Background Jobs
  4. Message Queue
  5. Apache Pulsar vs Sparrow

Apache Pulsar vs Sparrow

OverviewComparisonAlternatives

Overview

Sparrow
Sparrow
Stacks6
Followers11
Votes0
Apache Pulsar
Apache Pulsar
Stacks119
Followers199
Votes24

Sparrow vs Apache Pulsar: What are the differences?

Developers describe Sparrow as "A really fast lightweight queue written in Ruby that speaks memcache". Sparrow keeps messages in memory, but persists them to disk, using Sqlite, when the queue is shutdown. On the other hand, Apache Pulsar is detailed as "Distributed solution providing messaging and queuing for streaming data". Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.

Sparrow and Apache Pulsar belong to "Message Queue" category of the tech stack.

Apache Pulsar is an open source tool with 6.24K GitHub stars and 1.51K GitHub forks. Here's a link to Apache Pulsar's open source repository on GitHub.

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Detailed Comparison

Sparrow
Sparrow
Apache Pulsar
Apache Pulsar

Sparrow keeps messages in memory, but persists them to disk, using Sqlite, when the queue is shutdown.

Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.

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Unified model supporting pub-sub messaging and queuing; Easy scalability to millions of topics; Native multi-datacenter replication; Multi-language client API; Guaranteed data durability; Scalable distributed storage leveraging Apache BookKeeper
Statistics
Stacks
6
Stacks
119
Followers
11
Followers
199
Votes
0
Votes
24
Pros & Cons
No community feedback yet
Pros
  • 7
    Simple
  • 4
    Scalable
  • 3
    High-throughput
  • 2
    Geo-replication
  • 2
    Multi-tenancy
Cons
  • 1
    Not jms compliant
  • 1
    No guaranteed dliefvery
  • 1
    No one and only one delivery
  • 1
    LImited Language support(6)
  • 1
    Very few commercial vendors for support

What are some alternatives to Sparrow, Apache Pulsar?

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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