Software Alternatives, Accelerators & Startups

rsyslog VS logstash

Compare rsyslog VS logstash and see what are their differences

rsyslog logo rsyslog

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

logstash logo logstash

logstash is a tool for managing events and logs.
  • rsyslog Landing page
    Landing page //
    2023-10-01
  • logstash Landing page
    Landing page //
    2023-10-21

rsyslog features and specs

  • High Performance
    Rsyslog is designed for high performance, capable of processing thousands of messages per second and efficiently handling large volumes of log data.
  • Modular Architecture
    Its modular architecture allows for the addition of various plugins and modules to extend functionality and customize the logging system as needed.
  • Advanced Filtering
    Rsyslog offers advanced filtering capabilities, using both simple and complex filters to fine-tune which logs are collected and where they are sent.
  • Network Support
    It has strong support for remote logging via protocols such as TCP, UDP, and RELP, making it a robust solution for centralized logging.
  • Reliability
    Features such as disk-assisted queues and failover actions ensure that log messages are not lost, improving overall reliability.
  • Compatibility
    Rsyslog is compatible with existing syslog implementations and can drop-in replace older syslog daemons without significant changes.
  • Open Source
    Being open-source software, it is freely available for use and modification, supported by an active community.

Possible disadvantages of rsyslog

  • Complex Configuration
    The configuration syntax of rsyslog can be complex and unintuitive, requiring a steep learning curve for beginners.
  • Documentation Quality
    While comprehensive, the documentation can sometimes be difficult to navigate and understand, which might pose challenges for new users.
  • Resource Consumption
    Although efficient, rsyslog can be resource-intensive in certain configurations, potentially impacting system performance if not properly optimized.
  • Dependency Management
    Managing dependencies for various modules and plugins can be cumbersome and may require additional effort to ensure compatibility.
  • Version Inconsistency
    Different distributions might include various versions of rsyslog, leading to inconsistencies in features and behaviors across environments.

logstash features and specs

  • Flexible Data Collection
    Logstash supports a wide variety of inputs, filters, and outputs, enabling it to collect, process, and forward data from numerous sources with ease.
  • Real-Time Processing
    Logstash can process logs and event data in real-time, enabling quick aggregation, transformation, and forwarding for timely insights and actions.
  • Ecosystem Integration
    As part of the Elastic Stack, Logstash integrates seamlessly with Elasticsearch, Kibana, and Beats, providing a cohesive solution for data ingestion, storage, and visualization.
  • Built-In Plugins
    Logstash has a robust collection of built-in plugins for inputs, codecs, filters, and outputs, minimizing the need for custom development.
  • Scalability
    Logstash can be scaled horizontally by adding more instances, which allows it to handle higher data throughput as your needs grow.
  • Extensibility
    Logstash's plugin architecture allows for custom plugins to be developed, providing flexibility for specific use cases.

Possible disadvantages of logstash

  • Resource Intensive
    Logstash can be quite resource-heavy, consuming significant CPU and memory, which could lead to increased infrastructure costs.
  • Complex Configuration
    The configuration syntax can be complex and sometimes unintuitive, making it challenging for new users to set up and maintain.
  • Latency
    In certain scenarios, Logstash can introduce latency in data processing, which may not be suitable for all real-time applications.
  • Single Point of Failure
    If not properly architected with redundancy, Logstash can become a single point of failure in your data pipeline.
  • Limited Error Handling
    Logstash's error handling is not very robust, which can make it difficult to troubleshoot and resolve issues as they arise.
  • Learning Curve
    Due to its powerful features and flexibility, there is a steep learning curve associated with mastering Logstash.

Analysis of rsyslog

Overall verdict

  • Yes, rsyslog is considered a good logging tool, especially for those who need a flexible and powerful solution. Its continuous development and extensive feature set make it a reliable choice for system administrators and IT professionals looking to maintain effective log management and monitoring systems.

Why this product is good

  • Rsyslog is a highly versatile and reliable logging tool that is widely used in UNIX and Linux environments for gathering log data from various sources, processing it, and forwarding it to specified destinations. It is known for its ease of configuration, scalability, and compatibility with different protocols and formats. Its ability to handle high log volumes and support for dynamic configurations make it a popular choice for both small and large scale operations.

Recommended for

    Rsyslog is recommended for system administrators, IT professionals, and DevOps engineers who require robust logging capabilities. It is particularly suitable for enterprises and organizations that need to process and analyze large volumes of log data, as well as those who leverage complex IT infrastructures where advanced log manipulation and forwarding are necessary.

Analysis of logstash

Overall verdict

  • Yes, Logstash is generally regarded as a good solution for centralized data ingestion and transformation. Its seamless integration with Elasticsearch and Kibana makes it a preferred choice for organizations already utilizing the Elastic Stack. For those looking for a robust and scalable solution to handle diverse data processing tasks, Logstash offers a reliable and efficient option.

Why this product is good

  • Logstash is a powerful data processing tool that is part of the Elastic Stack, commonly known as the ELK Stack (Elasticsearch, Logstash, Kibana). It is praised for its ability to ingest, transform, and store data efficiently from a variety of sources simultaneously. Logstash is particularly effective in processing logs and event data, making it an integral component for organizations looking to leverage real-time analytics and centralized logging. Its versatility is augmented by a rich ecosystem of plugins that support diverse input, filter, and output options, enhancing its ability to handle complex data processing workflows.

Recommended for

    Logstash is recommended for organizations and teams that require a centralized, scalable solution for data collection and processing. It's particularly beneficial for IT and DevOps teams managing system logs, application logs, security events, and various other types of data. Companies already using Elasticsearch and Kibana will find Logstash to be a natural choice due to its seamless integration within the Elastic Stack ecosystem. Additionally, businesses aiming to implement real-time data analysis and monitoring will find Logstash a valuable tool to include in their infrastructure.

rsyslog videos

[LINUX] #11 Rsyslog Server Log Analyzer e Mysql

More videos:

  • Review - Ubuntu: How can I configure logrotate without having `/etc/logrotate.d/rsyslog`?

logstash videos

Visualizing Logs Using ElasticSearch, Logstash and Kibana

More videos:

  • Review - Security Onion with Elasticsearch, Logstash, and Kibana (ELK)

Category Popularity

0-100% (relative to rsyslog and logstash)
Monitoring Tools
34 34%
66% 66
Log Management
30 30%
70% 70
Security & Privacy
62 62%
38% 38
Performance Monitoring
0 0%
100% 100

User comments

Share your experience with using rsyslog and logstash. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare rsyslog and logstash

rsyslog Reviews

Best Log Management Tools: Useful Tools for Log Management, Monitoring, Analytics, and More
Rsyslog is a blazing-fast system built for log processing. It offers great performance benchmarks, tight security features, and a modular design for custom modifications. Rsyslog has grown from a singular logging system to be able to parse and sort logs from an extended range of sources, which it can then transform and provide an output to be used in dedicated log analysis...
Source: stackify.com

logstash Reviews

10 Best Open Source ETL Tools for Data Integration
A free and open source ETL tool, Logstash collects data from several sources, performs a transformation process, and sends the output back to your choice of data warehouse. It consists of pre-built filters and more than a hundred plugins to carry out the data process operations. No matter the format or the complexity of data, Logstash dynamically ingests, transforms, and...
Source: testsigma.com
11 Best FREE Open-Source ETL Tools in 2024
Logstash is an Open-Source Data Pipeline that extracts data from multiple data sources and transforms the source data and events and loads them into ElasticSearch, a JSON-based search, and analytics engine. It is part of the ELK Stack. The “E” stands for ElasticSearch and the “K” stands for Kibana, a Data Visualization engine.
Source: hevodata.com
10 Best Linux Monitoring Tools and Software to Improve Server Performance [2022 Comparison]
Lastly, the Elastic Stack (ELK Stack) is a well-known tool for Linux performance monitoring. It’s composed of Elasticsearch (full-text search), Logstash (a log aggregator), Kibana (visualization via graphs and charts), and Beats (lightweight metrics collectors and shippers).
Source: sematext.com
Top 10 Popular Open-Source ETL Tools for 2021
Logstash is an Open-Source Data Pipeline that extracts data from multiple data sources and transforms the source data and events and loads them into ElasticSearch, a JSON-based search, and analytics engine. It is part of the ELK Stack. The “E” stands for ElasticSearch and the “K” stands for Kibana, a Data Visualization engine.
Source: hevodata.com
Top ETL Tools For 2021...And The Case For Saying "No" To ETL
Logstash is an open source data processing pipeline that ingests data from multiple sources simultaneously, transforming the source data and store events into ElasticSearch by default. Logstash is part of an ELK stack. The E stands for Elasticsearch, a JSON-based search and analytics engine, and the K stands for Kibana, which enables data visualization.
Source: blog.panoply.io

What are some alternatives?

When comparing rsyslog and logstash, you can also consider the following products

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

Wazuh - Open Source Host and Endpoint Security

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

Fortinet FortiAnalyzer - Fortinet FortiAnalyzer is a powerful product for Security Fabric Analytics and Automation.

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

Sematext Logagent - Logagent is a robust, flexible, open-source, and cloud-native data shipper for Application, Server, and Container Logs.

OSZAR »