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Fluentd VS Apache Storm

Compare Fluentd VS Apache Storm and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Fluentd logo Fluentd

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

Apache Storm logo Apache Storm

Apache Storm is a free and open source distributed realtime computation system.
  • Fluentd Landing page
    Landing page //
    2018-09-30
  • Apache Storm Landing page
    Landing page //
    2019-03-11

Fluentd features and specs

  • Open Source
    Fluentd is an open-source data collector, meaning it is free to use and has a large community of contributors and users who can provide support and plugins.
  • Unified Logging Layer
    It provides a unified logging layer that can collect, filter, and distribute logs from various sources to various destinations, simplifying log management.
  • Extensibility
    Fluentd supports a wide range of plugins for inputs, outputs, filters, and parsers, making it highly extensible and customizable to fit specific needs.
  • High Performance
    It is designed to be high-performance and can handle large volumes of logs efficiently, which is crucial for enterprise environments.
  • Flexible Configuration
    Fluentd offers flexible and straightforward configuration, allowing users to define complex data pipelines with relative ease.
  • Support for Multiple Environments
    Fluentd supports cloud, on-premises, and hybrid environments, making it versatile for various deployment scenarios.

Possible disadvantages of Fluentd

  • Complexity
    The flexibility and extensibility of Fluentd can introduce complexity, requiring a steep learning curve for new users to master the tool.
  • Resource Intensive
    Fluentd can be resource-intensive, especially when dealing with large volumes of data, which may require robust infrastructure.
  • Plugin Compatibility
    While there are many plugins available, not all of them are always up-to-date or compatible with the latest versions of Fluentd, potentially causing integration issues.
  • Maintenance Overhead
    Managing Fluentd involves continuous monitoring, updating, and maintenance to ensure optimal performance and security, which could be resource-draining.
  • Documentation Gaps
    Although there is extensive documentation, some users report that it lacks deep insights and examples for advanced configurations, requiring additional research and community support.

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.

Fluentd videos

+ Add

How-to Ship Logs to Grafana Loki with Promtail, FluentD & Fluent-bit

More videos:

  • Review - OpenShift Commons Briefing #72: Cloud Native Logging with Fluentd
  • Review - Fluentd, the Open Source Data Collection tool

Apache Storm videos

+ Add

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 Fluentd and Apache Storm)

Fluentd

Apache Storm

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

User comments

Share your experience with using Fluentd and Apache Storm. 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 Fluentd and Apache Storm

Fluentd Reviews

11 Best Splunk Alternatives
The CloudFront-log plugin, for example, can be used to ingest logs from Amazon CloudFront, while the elasticsearch plugin can be used to route logs to Elasticsearch. Fluentd only provides ingestion and routing services, so you'll have to develop your log management solution from the ground up. Fluentd has become a popular alternative to Logstash, transforming ELK into EFK....
Source: www.ittsystems.com
Top 15 Kafka Alternatives Popular In 2021
Inputs and outputs have inbuilt support to buffer, load balance, timeout and retry instances. It has a unified logging layer in between the data sources. There are over 5000+ companies that rely on Fluentd and approximately collect logs from over 50000+ servers. It scraps logs from sources and sends them across to services like object storage, Elasticsearch, etc. it is...
Source: www.spec-india.com
Best Log Management Tools: Useful Tools for Log Management, Monitoring, Analytics, and More
Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure. Fluentd’s flagship feature is an extensive library of plugins which provide extended support and functionality for anything related to log and data management within a concise developer environment.
Source: stackify.com

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 more popular. It has been mentiond 11 times since March 2021. 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.

Fluentd mentions (0)

We have not tracked any mentions of Fluentd yet. Tracking of Fluentd recommendations started around Mar 2021.

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
View more

What are some alternatives?

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

logstash - logstash is a tool for managing events and logs.

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

Graylog - Graylog is an open source log management platform for collecting, indexing, and analyzing both structured and unstructured data.

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

rsyslog - Rsyslog is an enhanced syslogd supporting, among others, MySQL, PostgreSQL, failover log...

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

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