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  1. Stackups
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  3. Background Jobs
  4. Message Queue
  5. Apache NiFi vs Humanify

Apache NiFi vs Humanify

OverviewComparisonAlternatives

Overview

Apache NiFi
Apache NiFi
Stacks393
Followers692
Votes65
Humanify
Humanify
Stacks0
Followers1
Votes0
GitHub Stars7
Forks1

Apache NiFi vs Humanify: What are the differences?

Apache NiFi: A reliable system to process and distribute data. 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; 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..

Apache NiFi and Humanify are primarily classified as "Message Queue" and "Stream Processing" tools respectively.

Some of the features offered by Apache NiFi are:

  • Web-based user interface
  • Highly configurable
  • Data Provenance

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

Apache NiFi
Apache NiFi
Humanify
Humanify

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.

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.

Web-based user interface; Highly configurable; Data Provenance; Designed for extension; Secure
Simple installation; Fast data review; Human in the loop input; Open source
Statistics
GitHub Stars
-
GitHub Stars
7
GitHub Forks
-
GitHub Forks
1
Stacks
393
Stacks
0
Followers
692
Followers
1
Votes
65
Votes
0
Pros & Cons
Pros
  • 17
    Visual Data Flows using Directed Acyclic Graphs (DAGs)
  • 8
    Free (Open Source)
  • 7
    Simple-to-use
  • 5
    Reactive with back-pressure
  • 5
    Scalable horizontally as well as vertically
Cons
  • 2
    Memory-intensive
  • 2
    HA support is not full fledge
  • 1
    Kkk
No community feedback yet
Integrations
MongoDB
MongoDB
Amazon SNS
Amazon SNS
Amazon S3
Amazon S3
Linux
Linux
Amazon SQS
Amazon SQS
Kafka
Kafka
Apache Hive
Apache Hive
macOS
macOS
Node.js
Node.js

What are some alternatives to Apache NiFi, 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.

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.

IronMQ

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

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