Apache Storm vs RabbitMQ

Overview

RabbitMQ

Stacks21.8K

Followers18.9K

Votes558

GitHub Stars13.2K

Forks4.0K

Apache Storm

Stacks208

Followers282

Votes25

GitHub Stars6.7K

Forks4.1K

Apache Storm vs RabbitMQ: What are the differences?

Apache Storm and RabbitMQ are two popular technologies used for real-time data processing and messaging. Apache Storm is a real-time computation system while RabbitMQ is a message broker that enables communication between applications. Below are the key differences between Apache Storm and RabbitMQ:

Processing Model: Apache Storm uses a stream processing model where data is processed as it flows through the system in real-time. On the other hand, RabbitMQ follows a message queuing model where messages are stored in queues and processed sequentially.
Use Case: Apache Storm is commonly used for real-time analytics, event processing, and continuous computation tasks where low latency is critical. RabbitMQ, on the other hand, is often used for decoupling applications, asynchronous communication, and load balancing in distributed systems.
Scalability: Apache Storm is designed for horizontal scalability, meaning it can easily scale by adding more machines to the cluster. RabbitMQ, on the other hand, can be scaled vertically by upgrading hardware resources on a single machine.
Reliability: Apache Storm guarantees fault-tolerance through built-in mechanisms like tuple tracking and acking to ensure data processing reliability. RabbitMQ ensures message delivery reliability by persisting messages to disk and supporting message acknowledgments.
Complexity: Apache Storm can be more complex to set up and configure due to its distributed nature and real-time processing requirements. RabbitMQ, on the other hand, is generally easier to set up and use for simple messaging scenarios.
Message Delivery Guarantee: Apache Storm processes data in near real-time with no guarantee of message delivery, focusing on low latency. RabbitMQ, on the other hand, ensures message delivery through queues, even if the consumer is temporarily unavailable.

In Summary, Apache Storm focuses on real-time processing with a stream processing model, while RabbitMQ is a message broker designed for reliable asynchronous messaging and decoupling applications.

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Detailed Comparison

RabbitMQ	Apache Storm
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.	Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
Robust messaging for applications;Easy to use;Runs on all major operating systems;Supports a huge number of developer platforms;Open source and commercially supported	Storm integrates with the queueing and database technologies you already use;Simple API;Scalable;Fault tolerant;Guarantees data processing;Use with any language;Easy to deploy and operate;Free and open source
Statistics
GitHub Stars 13.2K	GitHub Stars 6.7K
GitHub Forks 4.0K	GitHub Forks 4.1K
Stacks 21.8K	Stacks 208
Followers 18.9K	Followers 282
Votes 558	Votes 25
Pros & Cons
Pros 235 It's fast and it works with good metrics/monitoring 80 Ease of configuration 60 I like the admin interface 52 Easy to set-up and start with 22 Durable Cons 9 Too complicated cluster/HA config and management 6 Needs Erlang runtime. Need ops good with Erlang runtime 5 Configuration must be done first, not by your code 4 Slow	Pros 10 Flexible 6 Easy setup 4 Event Processing 3 Clojure 2 Real Time

What are some alternatives to RabbitMQ, Apache Storm?

Kafka

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

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.

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

Related Comparisons

Apache Storm vs RabbitMQ: What are the differences?

Processing Model: Apache Storm uses a stream processing model where data is processed as it flows through the system in real-time. On the other hand, RabbitMQ follows a message queuing model where messages are stored in queues and processed sequentially.
Use Case: Apache Storm is commonly used for real-time analytics, event processing, and continuous computation tasks where low latency is critical. RabbitMQ, on the other hand, is often used for decoupling applications, asynchronous communication, and load balancing in distributed systems.
Scalability: Apache Storm is designed for horizontal scalability, meaning it can easily scale by adding more machines to the cluster. RabbitMQ, on the other hand, can be scaled vertically by upgrading hardware resources on a single machine.
Reliability: Apache Storm guarantees fault-tolerance through built-in mechanisms like tuple tracking and acking to ensure data processing reliability. RabbitMQ ensures message delivery reliability by persisting messages to disk and supporting message acknowledgments.
Complexity: Apache Storm can be more complex to set up and configure due to its distributed nature and real-time processing requirements. RabbitMQ, on the other hand, is generally easier to set up and use for simple messaging scenarios.
Message Delivery Guarantee: Apache Storm processes data in near real-time with no guarantee of message delivery, focusing on low latency. RabbitMQ, on the other hand, ensures message delivery through queues, even if the consumer is temporarily unavailable.

In Summary, Apache Storm focuses on real-time processing with a stream processing model, while RabbitMQ is a message broker designed for reliable asynchronous messaging and decoupling applications.

Apache Storm vs RabbitMQ

Overview