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  1. Stackups
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  3. Background Jobs
  4. Message Queue
  5. Amazon MQ vs StreamSets

Amazon MQ vs StreamSets

OverviewDecisionsComparisonAlternatives

Overview

StreamSets
StreamSets
Stacks53
Followers133
Votes0
Amazon MQ
Amazon MQ
Stacks55
Followers325
Votes12

Amazon MQ vs StreamSets: What are the differences?

Developers describe Amazon MQ as "Managed Message Broker Service for ActiveMQ". Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud. 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.

Amazon MQ can be classified as a tool in the "Message Queue" category, while StreamSets is grouped under "Data Science Tools".

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Advice on StreamSets, Amazon MQ

MITHIRIDI
MITHIRIDI

Software Engineer at LightMetrics

May 8, 2020

Needs adviceonAmazon SQSAmazon SQSAmazon MQAmazon 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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Comments

Detailed Comparison

StreamSets
StreamSets
Amazon MQ
Amazon MQ

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

Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud.

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
53
Stacks
55
Followers
133
Followers
325
Votes
0
Votes
12
Pros & Cons
Cons
  • 2
    No user community
  • 1
    Crashes
Pros
  • 7
    Supports low IQ developers
  • 3
    Supports existing protocols (JMS, NMS, AMQP, STOMP, …)
  • 2
    Easy to migrate existing messaging service
Cons
  • 4
    Slow AF
Integrations
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
AWS IAM
AWS IAM
Amazon CloudWatch
Amazon CloudWatch
ActiveMQ
ActiveMQ

What are some alternatives to StreamSets, Amazon MQ?

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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