Overview

NSQ

Stacks141

Followers356

Votes148

Scheduler API

Stacks5

Followers16

Votes0

NSQ vs Scheduler API: What are the differences?

<Write Introduction here>

1. **Scalability and Horizontality**: NSQ is designed to be distributed and horizontally scalable, allowing it to handle large amounts of messages efficiently across a cluster of machines. On the other hand, Scheduler API is more focused on scheduling and running tasks in a distributed environment rather than message handling.
   
2. **Reliability and Durability**: NSQ offers message queuing with features like configurable message retention periods and disk-backed storage, ensuring reliable message delivery. In contrast, Scheduler API is primarily used for task scheduling and does not have built-in features for message durability and reliability.
   
3. **Real-time vs Batch Processing**: NSQ is geared towards real-time message processing, enabling immediate consumption and processing of messages as they arrive. Scheduler API, on the other hand, is designed for batch processing of tasks at specified intervals or schedules, rather than real-time processing.

4. **Fault Tolerance and High Availability**: NSQ includes built-in fault tolerance mechanisms such as message re-queuing and distributed message routing to ensure high availability and reliability. In comparison, Scheduler API focuses more on ensuring tasks are executed as scheduled and may not have the same level of fault tolerance features as NSQ.

5. **Monitoring and Management**: NSQ provides extensive monitoring and management capabilities, with tools for real-time statistics, logging, and operational control of message queues. Scheduler API, being more task-centric, may not offer the same level of monitoring and management features for message queues.

6. **Community Support and Ecosystem**: NSQ has a larger community and ecosystem with a wider range of third-party integrations and plugins available, making it easier to extend and customize its functionality. Scheduler API, being more specialized for task scheduling, may have a smaller community and ecosystem with fewer plugins and integrations available.
   
In Summary, NSQ and Scheduler API differ in terms of scalability, reliability, real-time processing, fault tolerance, monitoring capabilities, and ecosystem support.

🔥 Trending in Background Jobs on StackShare

Solid Queue Background Jobs

Database-backed active job backend

Try it View Docs Alternatives

Try

0

1

Advice on NSQ, Scheduler API

Pramod

Co Founder at Usability Designs

Mar 2, 2020

Needs advice

I am looking into IoT World Solution where we have MQTT Broker. This MQTT Broker Sits in one of the Data Center. We are doing a lot of Alert and Alarm related processing on that Data, Currently, we are looking into Solution which can do distributed persistence of log/alert primarily on remote Disk.

Our primary need is to use lightweight where operational complexity and maintenance costs can be significantly reduced. We want to do it on-premise so we are not considering cloud solutions.

We looked into the following alternatives:

Apache Kafka - Great choice but operation and maintenance wise very complex. Rabbit MQ - High availability is the issue, Apache Pulsar - Operational Complexity. NATS - Absence of persistence. Akka Streams - Big learning curve and operational streams.

So we are looking into a lightweight library that can do distributed persistence preferably with publisher and subscriber model. Preferable on JVM stack.

572k views572k

Comments

Detailed Comparison

NSQ	Scheduler API
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.	It is a simple API to delay SQS messages. Call our APIs and we'll publish your messages when you need them.
support distributed topologies with no SPOF;horizontally scalable (no brokers, seamlessly add more nodes to the cluster);low-latency push based message delivery (performance);combination load-balanced and multicast style message routing;excel at both streaming (high-throughput) and job oriented (low-throughput) workloads;primarily in-memory (beyond a high-water mark messages are transparently kept on disk);runtime discovery service for consumers to find producers (nsqlookupd);transport layer security (TLS);data format agnostic;few dependencies (easy to deploy) and a sane, bounded, default configuration;simple TCP protocol supporting client libraries in any language;HTTP interface for stats, admin actions, and producers (no client library needed to publish);integrates with statsd for realtime instrumentation;robust cluster administration interface (nsqadmin)	scheduling ; cancelling scheduled SQS messages; changing the delay for already scheduled messages; checking the status of scheduled messages
Statistics
Stacks 141	Stacks 5
Followers 356	Followers 16
Votes 148	Votes 0
Pros & Cons
Pros 29 It's in golang 20 Distributed 20 Lightweight 18 Easy setup 17 High throughput Cons 1 Long term persistence 1 Get NSQ behavior out of Kafka but not inverse 1 HA	No community feedback yet

What are some alternatives to NSQ, Scheduler API?

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.

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.