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  5. Amazon WorkSpaces Streaming Protocol vs Confluent

Amazon WorkSpaces Streaming Protocol vs Confluent

OverviewComparisonAlternatives

Overview

Confluent
Confluent
Stacks337
Followers239
Votes14
Amazon WorkSpaces Streaming Protocol
Amazon WorkSpaces Streaming Protocol
Stacks0
Followers2
Votes0

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Detailed Comparison

Confluent
Confluent
Amazon WorkSpaces Streaming Protocol
Amazon WorkSpaces Streaming Protocol

It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream

It is a cloud-native streaming protocol that enables a consistent user experience when accessing your end user’s WorkSpaces across global distances and unreliable networks. It also enables additional features such as the beta feature of bi-directional video. As a cloud-native protocol, it delivers feature and performance enhancements without manual updates on your WorkSpaces.

Reliable; High-performance stream data platform; Manage and organize data from different sources.
Cloud-native protocol; Consistent user experience; Microservice architecture
Statistics
Stacks
337
Stacks
0
Followers
239
Followers
2
Votes
14
Votes
0
Pros & Cons
Pros
  • 4
    Free for casual use
  • 3
    No hypercloud lock-in
  • 3
    Dashboard for kafka insight
  • 2
    Easily scalable
  • 2
    Zero devops
Cons
  • 1
    Proprietary
No community feedback yet
Integrations
Microsoft SharePoint
Microsoft SharePoint
Java
Java
Python
Python
Salesforce Sales Cloud
Salesforce Sales Cloud
Kafka Streams
Kafka Streams
No integrations available

What are some alternatives to Confluent, Amazon WorkSpaces Streaming Protocol?

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.

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.

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