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Fluentd VS Apache Flink

Compare Fluentd VS Apache Flink and see what are their differences

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Fluentd logo Fluentd

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

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
  • Fluentd Landing page
    Landing page //
    2018-09-30
  • Apache Flink Landing page
    Landing page //
    2023-10-03

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 Flink features and specs

  • Real-time Stream Processing
    Apache Flink is designed for real-time data streaming, offering low-latency processing capabilities that are essential for applications requiring immediate data insights.
  • Event Time Processing
    Flink supports event time processing, which allows it to handle out-of-order events effectively and provide accurate results based on the time events actually occurred rather than when they were processed.
  • State Management
    Flink provides robust state management features, making it easier to maintain and query state across distributed nodes, which is crucial for managing long-running applications.
  • Fault Tolerance
    The framework includes built-in mechanisms for fault tolerance, such as consistent checkpoints and savepoints, ensuring high reliability and data consistency even in the case of failures.
  • Scalability
    Apache Flink is highly scalable, capable of handling both batch and stream processing workloads across a distributed cluster, making it suitable for large-scale data processing tasks.
  • Rich Ecosystem
    Flink has a rich set of APIs and integrations with other big data tools, such as Apache Kafka, Apache Hadoop, and Apache Cassandra, enhancing its versatility and ease of integration into existing data pipelines.

Possible disadvantages of Apache Flink

  • Complexity
    Flink’s advanced features and capabilities come with a steep learning curve, making it more challenging to set up and use compared to simpler stream processing frameworks.
  • Resource Intensive
    The framework can be resource-intensive, requiring substantial memory and CPU resources for optimal performance, which might be a concern for smaller setups or cost-sensitive environments.
  • Community Support
    While growing, the community around Apache Flink is not as large or mature as some other big data frameworks like Apache Spark, potentially limiting the availability of community-contributed resources and support.
  • Ecosystem Maturity
    Despite its integrations, the Flink ecosystem is still maturing, and certain tools and plugins may not be as developed or stable as those available for more established frameworks.
  • Operational Overhead
    Running and maintaining a Flink cluster can involve significant operational overhead, including monitoring, scaling, and troubleshooting, which might require a dedicated team or additional expertise.

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 Flink videos

+ Add

GOTO 2019 • Introduction to Stateful Stream Processing with Apache Flink • Robert Metzger

More videos:

  • Tutorial - Apache Flink Tutorial | Flink vs Spark | Real Time Analytics Using Flink | Apache Flink Training
  • Tutorial - How to build a modern stream processor: The science behind Apache Flink - Stefan Richter

Category Popularity

0-100% (relative to Fluentd and Apache Flink)

Fluentd

Apache Flink

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 Flink. 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 Flink

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 Flink Reviews

We have no reviews of Apache Flink yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Flink seems to be more popular. It has been mentiond 40 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 Flink mentions (40)

  • Is RisingWave the Next Apache Flink?
    Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / 12 days ago
  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 17 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / 22 days ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / 30 days ago
  • Exploring the Power and Community Behind Apache Flink
    In conclusion, Apache Flink is more than a big data processing tool—it is a thriving ecosystem that exemplifies the power of open source collaboration. From its impressive technical capabilities to its innovative funding model, Apache Flink shows that sustainable software development is possible when community, corporate support, and transparency converge. As industries continue to demand efficient real-time data... - Source: dev.to / 2 months ago
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What are some alternatives?

When comparing Fluentd and Apache Flink, 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.

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

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

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.

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