StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Fluentd vs Rsyslog

Fluentd vs Rsyslog

OverviewComparisonAlternatives

Overview

Rsyslog
Rsyslog
Stacks37
Followers75
Votes0
GitHub Stars2.2K
Forks700
Fluentd
Fluentd
Stacks630
Followers688
Votes39
GitHub Stars13.4K
Forks1.4K

Fluentd vs Rsyslog: What are the differences?

Fluentd vs Rsyslog

When it comes to log management and processing, Fluentd and Rsyslog are two popular options. While they both share some similarities, they also have several key differences.

  1. Architecture: Fluentd is built with a distributed architecture in mind, allowing it to scale horizontally by distributing the workload across multiple nodes. On the other hand, Rsyslog is designed to work in a client-server architecture, with centralized log processing and storage.

  2. Flexibility: Fluentd offers a high level of flexibility, supporting numerous input and output plugins, which enables it to collect and process logs from various sources and send them to various destinations. Rsyslog, on the other hand, has limited plugin support, making it less flexible in terms of log collection and distribution.

  3. Data Processing: Fluentd excels in providing extensive data processing capabilities. It allows for the application of filters and transformations on log data, facilitating custom parsing, tagging, and enrichment of the logs before they are forwarded. Rsyslog, on the other hand, focuses more on log aggregation and forwarding, with less emphasis on data processing.

  4. Logging Protocols: Fluentd primarily uses HTTP-based protocols for log communication, including both RESTful API and TCP/UDP protocols. Rsyslog, on the other hand, is built on the Syslog protocol, a standardized network protocol for log message exchange.

  5. Ecosystem: Fluentd benefits from a vibrant and active ecosystem, with a wide range of plugins and community support. This makes it easier to integrate Fluentd with other systems and leverage existing functionality. Rsyslog, while having a certain level of community support, has a comparatively smaller ecosystem.

  6. Ease of Use: Fluentd has a steeper learning curve due to its wide range of features and configuration options. It requires more technical expertise to set up and manage effectively. Rsyslog, on the other hand, is relatively easier to set up and configure, making it more suitable for simpler log management requirements.

In summary, Fluentd and Rsyslog differentiate themselves in terms of architecture, flexibility, data processing capabilities, logging protocols, ecosystem, and ease of use. The choice between the two depends on the specific requirements of the log management scenario and the technical expertise available.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

Rsyslog
Rsyslog
Fluentd
Fluentd

It offers high-performance, great security features and a modular design. It is able to accept inputs from a wide variety of sources, transform them, and output to the results to diverse destinations.

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.

Multi-threading; TCP, SSL, TLS, RELP; MySQL, PostgreSQL, Oracle and more; Filter any part of syslog message;
Open source; Flexible; Minimum resources; Reliable
Statistics
GitHub Stars
2.2K
GitHub Stars
13.4K
GitHub Forks
700
GitHub Forks
1.4K
Stacks
37
Stacks
630
Followers
75
Followers
688
Votes
0
Votes
39
Pros & Cons
No community feedback yet
Pros
  • 11
    Open-source
  • 10
    Great for Kubernetes node container log forwarding
  • 9
    Easy
  • 9
    Lightweight
Integrations
Oracle
Oracle
PostgreSQL
PostgreSQL
Splunk
Splunk
MySQL
MySQL
No integrations available

What are some alternatives to Rsyslog, Fluentd?

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Logentries

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Graylog

Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.

Sematext

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

ELK

ELK

It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

Sumo Logic

Sumo Logic

Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Related Comparisons

GitHub
Bitbucket

Bitbucket vs GitHub vs GitLab

GitHub
Bitbucket

AWS CodeCommit vs Bitbucket vs GitHub

Kubernetes
Rancher

Docker Swarm vs Kubernetes vs Rancher

gulp
Grunt

Grunt vs Webpack vs gulp

Graphite
Kibana

Grafana vs Graphite vs Kibana