Amazon SQS vs Apache Pulsar

Overview

Amazon SQS

Stacks2.8K

Followers2.0K

Votes171

Apache Pulsar

Stacks118

Followers199

Votes24

Amazon SQS vs Apache Pulsar: What are the differences?

Introduction

This Markdown document provides a comparison between Amazon Simple Queue Service (SQS) and Apache Pulsar, highlighting the key differences between the two messaging services.

Scalability: Amazon SQS is highly scalable and can handle a large number of messages per second, making it suitable for applications with high throughputs. On the other hand, Apache Pulsar offers topic-level scalability, allowing individual topics to handle high message rates independent of other topics in the system.
Latency: Amazon SQS generally has higher latency compared to Apache Pulsar. SQS is primarily designed for high durability and availability, sacrificing real-time responsiveness. Pulsar, on the other hand, offers low latency messaging with its distributed architecture and efficient message publication and consumption mechanisms.
Message Ordering: Amazon SQS offers ordered message processing within a single queue, ensuring that messages are delivered and processed in the order in which they were sent. In Apache Pulsar, message ordering is maintained within a single partition or topic, but not across multiple partitions or topics by default.
Event Time: Exactly Once Semantics: In Amazon SQS, the exactly-once processing of messages is not provided out of the box. It offers at-least-once message delivery, and deduplication mechanisms need to be implemented by the application developer. Apache Pulsar, on the other hand, provides built-in support for exactly-once semantics using event time in its log-based architecture.
Multi-tenancy: Amazon SQS is designed to be a fully isolated service with per-queue resource allocation, offering dedicated resources for each queue. In contrast, Apache Pulsar supports multi-tenancy by allowing multiple topics or namespaces to share the same cluster resources while maintaining data isolation.
Message Retention: Amazon SQS retains messages for a configurable period, but there is no built-in message retention mechanism beyond the configured retention period. Apache Pulsar provides configurable message retention policies at both the topic and cluster level, allowing message expiration and automatic cleanup based on time or size.

In Summary, Amazon SQS and Apache Pulsar have key differences in scalability, latency, message ordering, event time processing, multi-tenancy, and message retention. Each messaging service offers distinct features and trade-offs, allowing developers to choose the most suitable technology for their specific use cases.

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Advice on Amazon SQS, Apache Pulsar

MITHIRIDI

Software Engineer at LightMetrics

May 8, 2020

Needs adviceon

Amazon SQS

Amazon MQ

I want to schedule a message. Amazon SQS provides a delay of 15 minutes, but I want it in some hours.

Example: Let's say a Message1 is consumed by a consumer A but somehow it failed inside the consumer. I would want to put it in a queue and retry after 4hrs. Can I do this in Amazon MQ? I have seen in some Amazon MQ videos saying scheduling messages can be done. But, I'm not sure how.

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Detailed Comparison

Amazon SQS	Apache Pulsar
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.	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 queue can be created in any region.;The message payload can contain up to 256KB of text in any format. Each 64KB ‘chunk’ of payload is billed as 1 request. For example, a single API call with a 256KB payload will be billed as four requests.;Messages can be sent, received or deleted in batches of up to 10 messages or 256KB. Batches cost the same amount as single messages, meaning SQS can be even more cost effective for customers that use batching.;Long polling reduces extraneous polling to help you minimize cost while receiving new messages as quickly as possible. When your queue is empty, long-poll requests wait up to 20 seconds for the next message to arrive. Long poll requests cost the same amount as regular requests.;Messages can be retained in queues for up to 14 days.;Messages can be sent and read simultaneously.;Developers can get started with Amazon SQS by using only five APIs: CreateQueue, SendMessage, ReceiveMessage, ChangeMessageVisibility, and DeleteMessage. Additional APIs are available to provide advanced functionality.	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 2.8K	Stacks 118
Followers 2.0K	Followers 199
Votes 171	Votes 24
Pros & Cons
Pros 62 Easy to use, reliable 40 Low cost 28 Simple 14 Doesn't need to maintain it 8 It is Serverless Cons 2 Has a max message size (currently 256K) 2 Difficult to configure 2 Proprietary 1 Has a maximum 15 minutes of delayed messages only	Pros 7 Simple 4 Scalable 3 High-throughput 2 Geo-replication 2 Multi-tenancy Cons 1 No one and only one delivery 1 No guaranteed dliefvery 1 Not jms compliant 1 Only Supports Topics 1 LImited Language support(6)

What are some alternatives to Amazon SQS, 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.

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

Amazon SQS vs Apache Pulsar: What are the differences?

Introduction

This Markdown document provides a comparison between Amazon Simple Queue Service (SQS) and Apache Pulsar, highlighting the key differences between the two messaging services.

Scalability: Amazon SQS is highly scalable and can handle a large number of messages per second, making it suitable for applications with high throughputs. On the other hand, Apache Pulsar offers topic-level scalability, allowing individual topics to handle high message rates independent of other topics in the system.
Latency: Amazon SQS generally has higher latency compared to Apache Pulsar. SQS is primarily designed for high durability and availability, sacrificing real-time responsiveness. Pulsar, on the other hand, offers low latency messaging with its distributed architecture and efficient message publication and consumption mechanisms.
Message Ordering: Amazon SQS offers ordered message processing within a single queue, ensuring that messages are delivered and processed in the order in which they were sent. In Apache Pulsar, message ordering is maintained within a single partition or topic, but not across multiple partitions or topics by default.
Event Time: Exactly Once Semantics: In Amazon SQS, the exactly-once processing of messages is not provided out of the box. It offers at-least-once message delivery, and deduplication mechanisms need to be implemented by the application developer. Apache Pulsar, on the other hand, provides built-in support for exactly-once semantics using event time in its log-based architecture.
Multi-tenancy: Amazon SQS is designed to be a fully isolated service with per-queue resource allocation, offering dedicated resources for each queue. In contrast, Apache Pulsar supports multi-tenancy by allowing multiple topics or namespaces to share the same cluster resources while maintaining data isolation.
Message Retention: Amazon SQS retains messages for a configurable period, but there is no built-in message retention mechanism beyond the configured retention period. Apache Pulsar provides configurable message retention policies at both the topic and cluster level, allowing message expiration and automatic cleanup based on time or size.

Amazon SQS vs Apache Pulsar

Overview

Amazon SQS vs Apache Pulsar: What are the differences?