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  1. Stackups
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  4. Message Queue
  5. CloudAMQP vs StreamSets

CloudAMQP vs StreamSets

OverviewDecisionsComparisonAlternatives

Overview

CloudAMQP
CloudAMQP
Stacks62
Followers84
Votes7
StreamSets
StreamSets
Stacks53
Followers133
Votes0

CloudAMQP vs StreamSets: 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, StreamSets is detailed as "Where DevOps Meets Data Integration". The industry's first data operations platform for full life-cycle management of data in motion.

CloudAMQP can be classified as a tool in the "Message Queue" category, while StreamSets is grouped under "Data Science 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, StreamSets provides the following key features:

  • Build Batch & Streaming Pipelines in Hours
  • Map and Monitor Runtime Performance
  • Protect Sensitive Data as it Arrives

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Advice on CloudAMQP, StreamSets

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!

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Detailed Comparison

CloudAMQP
CloudAMQP
StreamSets
StreamSets

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

An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.

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.;
Only StreamSets provides a single design experience for all design patterns (batch, streaming, CDC, ETL, ELT, and ML pipelines) for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps.
Statistics
Stacks
62
Stacks
53
Followers
84
Followers
133
Votes
7
Votes
0
Pros & Cons
Pros
  • 4
    Some of the best customer support you'll ever find
  • 3
    Easy to provision
Cons
  • 2
    No user community
  • 1
    Crashes
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
HBase
HBase
Databricks
Databricks
Amazon Redshift
Amazon Redshift
MySQL
MySQL
gRPC
gRPC
Google BigQuery
Google BigQuery
Amazon Kinesis
Amazon Kinesis
Cassandra
Cassandra
Hadoop
Hadoop
Redis
Redis

What are some alternatives to CloudAMQP, StreamSets?

Kafka

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

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.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

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.

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