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Apache Storm VS Confluent

Compare Apache Storm VS Confluent and see what are their differences

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Apache Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.

Confluent logo Confluent

Confluent offers a real-time data platform built around Apache Kafka.
  • Apache Storm Landing page
    Landing page //
    2019-03-11
  • Confluent Landing page
    Landing page //
    2023-10-22

Apache Storm videos

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Apache Storm Tutorial For Beginners | Apache Storm Training | Apache Storm Example | Edureka

More videos:

  • Review - Developing Java Streaming Applications with Apache Storm
  • Review - Atom Text Editor Option - Real-Time Analytics with Apache Storm

Confluent videos

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1. Intro | Monitoring Kafka in Confluent Control Center

More videos:

  • Review - Jason Gustafson, Confluent: Revisiting Exactly One Semantics (EOS) | Bay Area Apache Kafka® Meetup
  • Review - CLEARER SKIN AFTER 1 USE‼️| Ancient Cosmetics Update✨| CONFLUENT & RETICULATED PAPILLOMATOSIS CURE?😩

Category Popularity

0-100% (relative to Apache Storm and Confluent)

Apache Storm

Confluent

Big Data
39 39%
Big Data
61% 61
Stream Processing
27 27%
Stream Processing
73% 73
Databases
100 100%
Databases
0% 0
Data Management
0 0%
Data Management
100% 100

User comments

Share your experience with using Apache Storm and Confluent. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Storm and Confluent

Apache Storm Reviews

Top 15 Kafka Alternatives Popular In 2021
Apache Storm is a recognized, distributed, open-source real-time computational system. It is free, simple to use, and helps in easily and accurately processing multiple data streams in real-time. Because of its simplicity, it can be utilized with any programming language and that is one reason it is a developer’s preferred choice. It is fast, scalable, and integrates well...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Storm is an open-source distributed real-time computational system for processing data streams. Similar to what Hadoop does for batch processing, Apache Storm does for unbounded streams of data in a reliable manner. Built by Twitter, Apache Storm specifically aims at the transformation of data streams. Storm has many use cases like real-time analytics, online machine...
Source: www.analyticsinsight.net

Confluent Reviews

We have no reviews of Confluent yet.
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Social recommendations and mentions

Based on our record, Apache Storm seems to be a lot more popular than Confluent. While we know about 11 links to Apache Storm, we've tracked only 1 mention of Confluent. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Storm mentions (11)

  • Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
    There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
  • Real Time Data Infra Stack
    Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 1 year ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 1 year ago
  • Elon Musk reportedly wants to fire 75% of Twitter’s employees
    Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 1 year ago
  • Spark for beginners - and you
    Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 2 years ago
View more

Confluent mentions (1)

  • Spring Boot Event Streaming with Kafka
    We’re going to setup a Kafka cluster using confluent.io, create a producer and consumer as well as enhance our behavior driven tests to include the new interface. We’re going to update our helm chart so that the updates are seamless to Kubernetes and we’re going to leverage our observability stack to propagate the traces in the published messages. Source: about 2 years ago

What are some alternatives?

When comparing Apache Storm and Confluent, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Spark Streaming - Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

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