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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. Confluent vs Humanify

Confluent vs Humanify

OverviewComparisonAlternatives

Overview

Confluent
Confluent
Stacks337
Followers239
Votes14
Humanify
Humanify
Stacks0
Followers1
Votes0
GitHub Stars7
Forks1

Confluent vs Humanify: What are the differences?

Confluent: A stream data platform to help companies harness their high volume real-time data streams. 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; Humanify: Add human touch to otherwise very machined node.js streams. It is a free and open source server and web application, written in Node.js, that allows adding human intelligence to data streaming in scenarios where computers are not suitable to make educated enough choices In just a couple lines of code it will ingest your data stream, open an HTTP server with a WebApplication that will be fed with all the data from the stream. Now you and your team can add decisions to each item of your data stream..

Confluent can be classified as a tool in the "Message Queue" category, while Humanify is grouped under "Stream Processing".

Some of the features offered by Confluent are:

  • Reliable
  • High-performance stream data platform
  • Manage and organize data from different sources.

On the other hand, Humanify provides the following key features:

  • Simple installation
  • Fast data review
  • Human in the loop input

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Detailed Comparison

Confluent
Confluent
Humanify
Humanify

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 free and open source server and web application, written in Node.js, that allows adding human intelligence to data streaming in scenarios where computers are not suitable to make educated enough choices. In just a couple lines of code it will ingest your data stream, open an HTTP server with a WebApplication that will be fed with all the data from the stream. Now you and your team can add decisions to each item of your data stream.

Reliable; High-performance stream data platform; Manage and organize data from different sources.
Simple installation; Fast data review; Human in the loop input; Open source
Statistics
GitHub Stars
-
GitHub Stars
7
GitHub Forks
-
GitHub Forks
1
Stacks
337
Stacks
0
Followers
239
Followers
1
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
Node.js
Node.js

What are some alternatives to Confluent, Humanify?

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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