AWS DataOps Development Kit vs RabbitMQ
Overview
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CLI (Node.js)
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Detailed Comparison
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received. | It is an open source development framework for customers that build data workflows and modern data architecture on AWS. It offers high-level abstractions allowing you to build pipelines that manage data flows on AWS, driven by DevOps best practices. |
Robust messaging for applications;Easy to use;Runs on all major operating systems;Supports a huge number of developer platforms;Open source and commercially supported | Open source development framework;
Build data workflows and modern data architecture;
Extensible;
Offers high-level abstractions |
Statistics | |
GitHub Stars 13.2K | GitHub Stars 271 |
GitHub Forks 4.0K | GitHub Forks 25 |
Stacks 21.8K | Stacks 1 |
Followers 18.9K | Followers 1 |
Votes 558 | Votes 0 |
Pros & Cons | |
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Cons
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Integrations | |
| No integrations available | |
What are some alternatives to RabbitMQ, AWS DataOps Development Kit?
Kafka
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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.
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
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.
Presto
Distributed SQL Query Engine for Big Data
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.
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
