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Apache Flume VS Apache Storm

Compare Apache Flume VS Apache Storm and see what are their differences

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Apache Flume logo Apache Flume

Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data

Apache Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.
  • Apache Flume Landing page
    Landing page //
    2018-09-29
  • Apache Storm Landing page
    Landing page //
    2019-03-11

Apache Flume features and specs

No features have been listed yet.

Apache Storm features and specs

  • Real-Time Processing
    Apache Storm is designed for processing data in real-time, which makes it ideal for applications like fraud detection, recommendation systems, and monitoring tools.
  • Scalability
    Storm is capable of scaling horizontally, allowing it to handle increasing amounts of data by adding more nodes, making it suitable for large-scale applications.
  • Fault Tolerance
    Storm provides robust fault-tolerance mechanisms by rerouting tasks from failed nodes to operational ones, ensuring continuous processing.
  • Broad Language Support
    Apache Storm supports multiple programming languages, including Java, Python, and Ruby, allowing developers to use the language they are most comfortable with.
  • Open Source Community
    Being an Apache project, Storm benefits from a strong open-source community, which contributes to its development and offers abundant resources and support.

Possible disadvantages of Apache Storm

  • Complex Setup
    Setting up and configuring Apache Storm can be complex and time-consuming, requiring detailed knowledge of its architecture and the underlying infrastructure.
  • High Learning Curve
    The architecture and components of Storm can be difficult for new users to grasp, leading to a steeper learning curve compared to some other streaming platforms.
  • Maintenance Overhead
    Managing and maintaining a Storm cluster can require significant effort, including monitoring, troubleshooting, and scaling the infrastructure.
  • Error Handling
    While Storm is fault-tolerant, its error handling at the application level can sometimes be challenging, requiring careful design to manage failures effectively.
  • Resource Intensive
    Storm can be resource-intensive, particularly in terms of memory and CPU usage, which can lead to increased costs and necessitate powerful hardware.

Apache Flume videos

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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

Category Popularity

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

Apache Flume

Apache Storm

Log Management
100 100%
Log Management
0% 0
Big Data
19 19%
Big Data
81% 81
Monitoring Tools
100 100%
Monitoring Tools
0% 0
Stream Processing
0 0%
Stream Processing
100% 100

User comments

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Reviews

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

Apache Flume Reviews

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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

Social recommendations and mentions

Based on our record, Apache Storm seems to be a lot more popular than Apache Flume. While we know about 11 links to Apache Storm, we've tracked only 1 mention of Apache Flume. 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 Flume mentions (1)

  • 7 Open-Source Log Management Tools that you may consider in 2023
    Apache Flume is an open-source log management tool designed to efficiently collect, aggregate, and transport large volumes of log data from various sources to a centralized data store, such as HDFS or Hbase. It excels in handling large amounts of log data in real-time and is highly scalable, able to handle the load from multiple servers, network devices, and applications. - Source: dev.to / over 2 years ago

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 2 years 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 2 years ago
  • In One Minute : Hadoop
    Storm, a system for real-time and stream processing. - Source: dev.to / over 2 years 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 2 years 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 3 years ago
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What are some alternatives?

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

Fluentd - Fluentd is a cross platform open source data collection solution originally developed at Treasure Data.

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

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

Splunk - Splunk's operational intelligence platform helps unearth intelligent insights from machine data.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

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