RSMQ vs Redis

Overview

Redis

Stacks61.9K

Followers46.5K

Votes3.9K

GitHub Stars42

Forks6

RSMQ

Stacks4

Followers87

Votes6

GitHub Stars1.8K

Forks120

RSMQ vs Redis: What are the differences?

Data Structure: The key difference between RSMQ and Redis is their primary data structure. RSMQ is a message queue built on top of Redis, utilizing lists and sets to store messages and message metadata. On the other hand, Redis is a high-performance in-memory data store that supports various data structures such as strings, lists, sets, sorted sets, and hashes.
Purpose: RSMQ is specifically designed for message queuing, providing features like message visibility timeout and delayed message delivery. In contrast, Redis is a versatile data store used for caching, session storage, real-time analytics, and more, aside from message queuing capabilities.
Performance: RSMQ is optimized for message queuing operations and offers efficient message insertion, retrieval, and deletion. Redis, on the other hand, provides excellent performance across different data access patterns but may not offer the same level of optimization for message queuing as RSMQ.
Management Overhead: Setting up and managing RSMQ typically involves less complexity compared to configuring and maintaining a standalone Redis instance. This is because RSMQ abstracts away much of the underlying Redis setup required for message queuing operations.
Ease of Use: RSMQ is designed to be simple to use for basic message queuing tasks, with a focus on minimal configuration and ease of integration. In contrast, while Redis offers more advanced features and flexibility, it may require additional effort and expertise to harness its full potential.
Scalability: When it comes to scalability, Redis shines with its built-in support for clustering and data replication, making it suitable for large-scale distributed systems. While RSMQ can also be scaled horizontally by deploying multiple instances, it may not offer the same level of scalability and redundancy features as native Redis clustering capabilities.

In Summary, RSMQ and Redis differ in their primary data structure, purpose, performance, management overhead, ease of use, and scalability.

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CLI (Node.js)

Manual

Detailed Comparison

Redis	RSMQ
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.	tl;dr: If you run a Redis server and currently use Amazon SQS or a similar message queue you might as well use this fast little replacement. Using a shared Redis server multiple Node.js processes can send / receive messages.
-	Lightweight: Just Redis and ~500 lines of javascript.;Guaranteed delivery of a message to exactly one recipient within a messages visibility timeout.;Received messages that are not deleted will reappear after the visibility timeout.;Test coverage;Optional RESTful interface via rest-rsmq
Statistics
GitHub Stars 42	GitHub Stars 1.8K
GitHub Forks 6	GitHub Forks 120
Stacks 61.9K	Stacks 4
Followers 46.5K	Followers 87
Votes 3.9K	Votes 6
Pros & Cons
Pros 888 Performance 542 Super fast 514 Ease of use 444 In-memory cache 324 Advanced key-value cache Cons 15 Cannot query objects directly 3 No secondary indexes for non-numeric data types 1 No WAL	Pros 2 Simple, does one thing well 1 Comes with a visibility timeout feature similar to AWS 1 Written in TypeScript 1 Backed by Redis 1 Written in Coffeescript

What are some alternatives to Redis, RSMQ?

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.

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

Related Comparisons

RSMQ vs Redis: What are the differences?

Data Structure: The key difference between RSMQ and Redis is their primary data structure. RSMQ is a message queue built on top of Redis, utilizing lists and sets to store messages and message metadata. On the other hand, Redis is a high-performance in-memory data store that supports various data structures such as strings, lists, sets, sorted sets, and hashes.
Purpose: RSMQ is specifically designed for message queuing, providing features like message visibility timeout and delayed message delivery. In contrast, Redis is a versatile data store used for caching, session storage, real-time analytics, and more, aside from message queuing capabilities.
Performance: RSMQ is optimized for message queuing operations and offers efficient message insertion, retrieval, and deletion. Redis, on the other hand, provides excellent performance across different data access patterns but may not offer the same level of optimization for message queuing as RSMQ.
Management Overhead: Setting up and managing RSMQ typically involves less complexity compared to configuring and maintaining a standalone Redis instance. This is because RSMQ abstracts away much of the underlying Redis setup required for message queuing operations.
Ease of Use: RSMQ is designed to be simple to use for basic message queuing tasks, with a focus on minimal configuration and ease of integration. In contrast, while Redis offers more advanced features and flexibility, it may require additional effort and expertise to harness its full potential.
Scalability: When it comes to scalability, Redis shines with its built-in support for clustering and data replication, making it suitable for large-scale distributed systems. While RSMQ can also be scaled horizontally by deploying multiple instances, it may not offer the same level of scalability and redundancy features as native Redis clustering capabilities.

In Summary, RSMQ and Redis differ in their primary data structure, purpose, performance, management overhead, ease of use, and scalability.

RSMQ vs Redis

Overview