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CommentsApache Flink vs CloudAMQP
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Advice on CloudAMQP, Apache Flink
Detailed Comparison
Fully managed, highly available RabbitMQ servers and clusters, on all major compute platforms. | Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala. |
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.;
| Hybrid batch/streaming runtime that supports batch processing and data streaming programs.;Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.;Flexible and expressive windowing semantics for data stream programs;Built-in program optimizer that chooses the proper runtime operations for each program;Custom type analysis and serialization stack for high performance |
Statistics | |
GitHub Stars - | GitHub Stars 25.4K |
GitHub Forks - | GitHub Forks 13.7K |
Stacks 62 | Stacks 534 |
Followers 84 | Followers 879 |
Votes 7 | Votes 38 |
Pros & Cons | |
Pros
| Pros
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Integrations | |
What are some alternatives to CloudAMQP, Apache Flink?
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.
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.
