Apache Pulsar vs Hutch

Overview

Hutch

Stacks7

Followers9

Votes0

Apache Pulsar

Stacks119

Followers199

Votes24

Apache Pulsar vs Hutch: What are the differences?

Apache Pulsar and Hutch are both messaging systems used for real-time data processing and streaming applications. However, there are key differences between the two technologies that set them apart.

Scalability: Apache Pulsar is designed to be horizontally scalable by distributing topics across multiple brokers, allowing for better throughput and availability as the load increases. On the other hand, Hutch is more suitable for small-scale applications and struggles to scale efficiently when dealing with large volumes of data.
Message Durability: Apache Pulsar provides durable message storage using Apache BookKeeper, ensuring that messages are not lost even in the event of broker failures. Hutch, on the other hand, relies on disk-based storage which might compromise message durability in certain failure scenarios.
Message Ordering: Apache Pulsar guarantees message ordering at both the topic and partition level, ensuring that messages are processed in the order they were published. In contrast, Hutch does not provide strong ordering guarantees, which can lead to potential issues in certain use cases that require strict message sequencing.
Geo-Replication: Apache Pulsar supports built-in geo-replication for disaster recovery and data locality purposes, allowing messages to be replicated across multiple data centers. Hutch lacks native support for geo-replication, which can be a limitation for applications that require this feature.
Integration: Apache Pulsar offers seamless integration with popular streaming frameworks such as Apache Flink and Apache Spark, making it easier to build real-time data processing pipelines. Hutch, on the other hand, has limited integration options with other streaming technologies, which can hinder the flexibility and extensibility of the system.

In Summary, Apache Pulsar provides superior scalability, message durability, ordering guarantees, geo-replication, and integration capabilities compared to Hutch, making it a more suitable choice for demanding real-time data processing applications.

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CLI (Node.js)

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Detailed Comparison

Hutch	Apache Pulsar
Hutch is a Ruby library for enabling asynchronous inter-service communication in a service-oriented architecture, using RabbitMQ.	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.
A simple way to define consumers (queues are automatically created and bound to the exchange with the appropriate binding keys);An executable and CLI for running consumers (akin to rake resque:work);Automatic setup of the central exchange;Sensible out-of-the-box configuration (e.g. durable messages, persistent queues, message acknowledgements);Management of queue subscriptions;Rails integration;Configurable exception handling	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 7	Stacks 119
Followers 9	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
Integrations
RabbitMQ	No integrations available

What are some alternatives to Hutch, Apache Pulsar?

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

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

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 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

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

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

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 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

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

Related Comparisons

Apache Pulsar vs Hutch: What are the differences?

Apache Pulsar and Hutch are both messaging systems used for real-time data processing and streaming applications. However, there are key differences between the two technologies that set them apart.

Scalability: Apache Pulsar is designed to be horizontally scalable by distributing topics across multiple brokers, allowing for better throughput and availability as the load increases. On the other hand, Hutch is more suitable for small-scale applications and struggles to scale efficiently when dealing with large volumes of data.
Message Durability: Apache Pulsar provides durable message storage using Apache BookKeeper, ensuring that messages are not lost even in the event of broker failures. Hutch, on the other hand, relies on disk-based storage which might compromise message durability in certain failure scenarios.
Message Ordering: Apache Pulsar guarantees message ordering at both the topic and partition level, ensuring that messages are processed in the order they were published. In contrast, Hutch does not provide strong ordering guarantees, which can lead to potential issues in certain use cases that require strict message sequencing.
Geo-Replication: Apache Pulsar supports built-in geo-replication for disaster recovery and data locality purposes, allowing messages to be replicated across multiple data centers. Hutch lacks native support for geo-replication, which can be a limitation for applications that require this feature.
Integration: Apache Pulsar offers seamless integration with popular streaming frameworks such as Apache Flink and Apache Spark, making it easier to build real-time data processing pipelines. Hutch, on the other hand, has limited integration options with other streaming technologies, which can hinder the flexibility and extensibility of the system.

Apache Pulsar vs Hutch

Overview