Confluent vs Heron

Overview

Heron

Stacks22

Followers63

Votes4

Confluent

Stacks337

Followers239

Votes14

Heron vs Confluent: What are the differences?

Developers describe Heron as "Realtime, distributed, fault-tolerant stream processing engine from Twitter". Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements. On the other hand, Confluent is detailed as "We make 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.

Heron and Confluent can be categorized as "Stream Processing" tools.

Heron is an open source tool with 3.39K GitHub stars and 601 GitHub forks. Here's a link to Heron's open source repository on GitHub.

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Detailed Comparison

Heron	Confluent
Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements.	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
-	Reliable; High-performance stream data platform; Manage and organize data from different sources.
Statistics
Stacks 22	Stacks 337
Followers 63	Followers 239
Votes 4	Votes 14
Pros & Cons
Pros 1 Operation friendly 1 Highly Customizable 1 Support most popular container environment 1 Realtime Stream Processing	Pros 4 Free for casual use 3 No hypercloud lock-in 3 Dashboard for kafka insight 2 Zero devops 2 Easily scalable Cons 1 Proprietary
Integrations
No integrations available	Microsoft SharePoint Java Python Salesforce Sales Cloud Kafka Streams

What are some alternatives to Heron, Confluent?

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.

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.

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 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

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.