Azure Service Bus vs Confluent

Overview

Azure Service Bus

Stacks553

Followers536

Votes7

Confluent

Stacks337

Followers239

Votes14

Azure Service Bus vs Confluent: What are the differences?

Introduction: When comparing Azure Service Bus and Confluent, it is essential to understand the key differences between these two messaging services that are commonly used in the industry.

Protocol Support: Azure Service Bus mainly supports AMQP and MQTT protocols, while Confluent focuses on Apache Kafka, which uses the Kafka protocol. This difference in protocol support can impact compatibility and integration with other systems or applications.
Ecosystem Integration: Azure Service Bus is tightly integrated with other Azure services, providing a seamless experience for users within the Azure ecosystem. On the other hand, Confluent integrates well with the broader Kafka ecosystem, enabling easy interoperability with various data processing frameworks and tools.
Persistence Mechanism: Azure Service Bus offers reliable message retention using durable storage, ensuring that messages are not lost during transient failures. Confluent, being built on top of Kafka, leverages Kafka's high-throughput, fault-tolerant architecture for persistence.
Scalability: Azure Service Bus can scale vertically by increasing resources, but it has limitations on horizontal scaling. Confluent, utilizing Kafka's distributed architecture, can easily scale horizontally by adding more brokers to the cluster to handle increased message throughput.
Message Delivery Semantics: Azure Service Bus supports both at-least-once and exactly-once message delivery semantics, allowing users to choose the level of guarantee required for their messaging scenarios. Confluent, following Kafka's philosophy, emphasizes on at-least-once delivery semantics, ensuring fault-tolerance and data integrity.

In Summary, understanding the key differences such as protocol support, ecosystem integration, persistence mechanism, scalability, and message delivery semantics between Azure Service Bus and Confluent is crucial for selecting the most suitable messaging service for a particular use case.

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Advice on Azure Service Bus, Confluent

André

Technology Manager at GS1 Portugal - Codipor

Jul 30, 2020

Needs adviceon

.NET Core

Hello dear developers, our company is starting a new project for a new Web App, and we are currently designing the Architecture (we will be using .NET Core). We want to embark on something new, so we are thinking about migrating from a monolithic perspective to a microservices perspective. We wish to containerize those microservices and make them independent from each other. Is it the best way for microservices to communicate with each other via ESB, or is there a new way of doing this? Maybe complementing with an API Gateway? Can you recommend something else different than the two tools I provided?

We want something good for Cost/Benefit; performance should be high too (but not the primary constraint).

Thank you very much in advance :)

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Comments

Detailed Comparison

Azure Service Bus	Confluent
It is a cloud messaging system for connecting apps and devices across public and private clouds. You can depend on it when you need highly-reliable cloud messaging service between applications and services, even when one or more is offline.	It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream
-	Reliable; High-performance stream data platform; Manage and organize data from different sources.
Statistics
Stacks 553	Stacks 337
Followers 536	Followers 239
Votes 7	Votes 14
Pros & Cons
Pros 4 Easy Integration with .Net 2 Cloud Native 1 Use while high messaging need Cons 1 Observability of messages in the queue is lacking 1 Lacking in JMS support 1 Skills can only be used in Azure - vendor lock-in 1 Limited features in Basic tier	Pros 4 Free for casual use 3 No hypercloud lock-in 3 Dashboard for kafka insight 2 Zero devops 2 Easily scalable Cons 1 Proprietary
Integrations
No integrations available	Microsoft SharePoint Java Python Salesforce Sales Cloud Kafka Streams

What are some alternatives to Azure Service Bus, Confluent?

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

Azure Service Bus vs Confluent: What are the differences?

Introduction: When comparing Azure Service Bus and Confluent, it is essential to understand the key differences between these two messaging services that are commonly used in the industry.

Protocol Support: Azure Service Bus mainly supports AMQP and MQTT protocols, while Confluent focuses on Apache Kafka, which uses the Kafka protocol. This difference in protocol support can impact compatibility and integration with other systems or applications.
Ecosystem Integration: Azure Service Bus is tightly integrated with other Azure services, providing a seamless experience for users within the Azure ecosystem. On the other hand, Confluent integrates well with the broader Kafka ecosystem, enabling easy interoperability with various data processing frameworks and tools.
Persistence Mechanism: Azure Service Bus offers reliable message retention using durable storage, ensuring that messages are not lost during transient failures. Confluent, being built on top of Kafka, leverages Kafka's high-throughput, fault-tolerant architecture for persistence.
Scalability: Azure Service Bus can scale vertically by increasing resources, but it has limitations on horizontal scaling. Confluent, utilizing Kafka's distributed architecture, can easily scale horizontally by adding more brokers to the cluster to handle increased message throughput.
Message Delivery Semantics: Azure Service Bus supports both at-least-once and exactly-once message delivery semantics, allowing users to choose the level of guarantee required for their messaging scenarios. Confluent, following Kafka's philosophy, emphasizes on at-least-once delivery semantics, ensuring fault-tolerance and data integrity.

Azure Service Bus vs Confluent

Overview