Apache NiFi vs Storm

Overview

Apache Storm

Stacks207

Followers282

Votes25

GitHub Stars6.7K

Forks4.1K

Apache NiFi

Stacks393

Followers692

Votes65

Apache NiFi vs Storm: What are the differences?

Developers describe Apache NiFi as "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. On the other hand, Storm is detailed as "Distributed and fault-tolerant realtime computation". Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.

Apache NiFi and Storm can be categorized as "Stream Processing" tools.

Storm is an open source tool with 5.75K GitHub stars and 3.91K GitHub forks. Here's a link to Storm's open source repository on GitHub.

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Detailed Comparison

Apache Storm	Apache NiFi
Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.	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.
Storm integrates with the queueing and database technologies you already use;Simple API;Scalable;Fault tolerant;Guarantees data processing;Use with any language;Easy to deploy and operate;Free and open source	Web-based user interface; Highly configurable; Data Provenance; Designed for extension; Secure
Statistics
GitHub Stars 6.7K	GitHub Stars -
GitHub Forks 4.1K	GitHub Forks -
Stacks 207	Stacks 393
Followers 282	Followers 692
Votes 25	Votes 65
Pros & Cons
Pros 10 Flexible 6 Easy setup 4 Event Processing 3 Clojure 2 Real Time	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
Integrations
No integrations available	MongoDB Amazon SNS Amazon S3 Linux Amazon SQS Kafka Apache Hive macOS

What are some alternatives to Apache Storm, Apache NiFi?

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.

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.

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.