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  5. CloudAMQP vs Kafka vs apache nifi

CloudAMQP vs Kafka vs apache nifi

OverviewDecisionsComparisonAlternatives

Overview

CloudAMQP
CloudAMQP
Stacks62
Followers84
Votes7
Kafka
Kafka
Stacks24.2K
Followers22.3K
Votes607
GitHub Stars31.2K
Forks14.8K

CloudAMQP vs Kafka: What are the differences?

Developers describe CloudAMQP as "RabbitMQ as a Service". Fully managed, highly available RabbitMQ servers and clusters, on all major compute platforms. On the other hand, Kafka is detailed as "Distributed, fault tolerant, high throughput pub-sub messaging system". Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

CloudAMQP and Kafka can be primarily classified as "Message Queue" tools.

Some of the features offered by CloudAMQP are:

  • Support - 24/7 support, via email, chat and phone.
  • Real time metrics and alarms - Get notified in advanced when your queues are growing faster than you're consuming them, when you're servers are over loaded etc. and take action before it becomes a problem.
  • Auto-healing - Our monitoring systems automatically detects and fixes a lot of problems such as kernel bugs, auto-restarts, RabbitMQ/Erlang version upgrades etc.

On the other hand, Kafka provides the following key features:

  • Written at LinkedIn in Scala
  • Used by LinkedIn to offload processing of all page and other views
  • Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)

"Some of the best customer support you'll ever find" is the primary reason why developers consider CloudAMQP over the competitors, whereas "High-throughput" was stated as the key factor in picking Kafka.

Kafka is an open source tool with 13.1K GitHub stars and 6.99K GitHub forks. Here's a link to Kafka's open source repository on GitHub.

According to the StackShare community, Kafka has a broader approval, being mentioned in 691 company stacks & 2398 developers stacks; compared to CloudAMQP, which is listed in 17 company stacks and 15 developer stacks.

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Advice on CloudAMQP, Kafka

viradiya
viradiya

Apr 12, 2020

Needs adviceonAngularJSAngularJSASP.NET CoreASP.NET CoreMSSQLMSSQL

We are going to develop a microservices-based application. It consists of AngularJS, ASP.NET Core, and MSSQL.

We have 3 types of microservices. Emailservice, Filemanagementservice, Filevalidationservice

I am a beginner in microservices. But I have read about RabbitMQ, but come to know that there are Redis and Kafka also in the market. So, I want to know which is best.

933k views933k
Comments
Ishfaq
Ishfaq

Feb 28, 2020

Needs advice

Our backend application is sending some external messages to a third party application at the end of each backend (CRUD) API call (from UI) and these external messages take too much extra time (message building, processing, then sent to the third party and log success/failure), UI application has no concern to these extra third party messages.

So currently we are sending these third party messages by creating a new child thread at end of each REST API call so UI application doesn't wait for these extra third party API calls.

I want to integrate Apache Kafka for these extra third party API calls, so I can also retry on failover third party API calls in a queue(currently third party messages are sending from multiple threads at the same time which uses too much processing and resources) and logging, etc.

Question 1: Is this a use case of a message broker?

Question 2: If it is then Kafka vs RabitMQ which is the better?

804k views804k
Comments
Mickael
Mickael

DevOps Engineer at Rookout

Mar 1, 2020

Decided

In addition to being a lot cheaper, Google Cloud Pub/Sub allowed us to not worry about maintaining any more infrastructure that needed.

We moved from a self-hosted RabbitMQ over to CloudAMQP and decided that since we use GCP anyway, why not try their managed PubSub?

It is one of the better decisions that we made, and we can just focus about building more important stuff!

472k views472k
Comments

Detailed Comparison

CloudAMQP
CloudAMQP
Kafka
Kafka

Fully managed, highly available RabbitMQ servers and clusters, on all major compute platforms.

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

Support - 24/7 support, via email, chat and phone.; Real time metrics and alarms - Get notified in advanced when your queues are growing faster than you're consuming them, when you're servers are over loaded etc. and take action before it becomes a problem.; Auto-healing - Our monitoring systems automatically detects and fixes a lot of problems such as kernel bugs, auto-restarts, RabbitMQ/Erlang version upgrades etc.; Metrics - Of course the default RabbitMQ interface is available, which gives you great inspection capabilities of your queues and message throughput, but we also gives you CPU, RAM and disk graphs to help you monitor the health and resource consumption of your clusters.;
Written at LinkedIn in Scala;Used by LinkedIn to offload processing of all page and other views;Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled);Supports both on-line as off-line processing
Statistics
GitHub Stars
-
GitHub Stars
31.2K
GitHub Forks
-
GitHub Forks
14.8K
Stacks
62
Stacks
24.2K
Followers
84
Followers
22.3K
Votes
7
Votes
607
Pros & Cons
Pros
  • 4
    Some of the best customer support you'll ever find
  • 3
    Easy to provision
Pros
  • 126
    High-throughput
  • 119
    Distributed
  • 92
    Scalable
  • 86
    High-Performance
  • 66
    Durable
Cons
  • 32
    Non-Java clients are second-class citizens
  • 29
    Needs Zookeeper
  • 9
    Operational difficulties
  • 5
    Terrible Packaging
Integrations
AppHarbor
AppHarbor
Google Compute Engine
Google Compute Engine
Heroku
Heroku
DigitalOcean
DigitalOcean
Amazon EC2
Amazon EC2
Red Hat OpenShift
Red Hat OpenShift
SoftLayer
SoftLayer
dotCloud
dotCloud
Pivotal Web Services (PWS)
Pivotal Web Services (PWS)
AppFog
AppFog
No integrations available

What are some alternatives to CloudAMQP, Kafka?

RabbitMQ

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

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

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

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

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

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

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

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

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

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.

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