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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Filebeat vs Graylog

Filebeat vs Graylog

OverviewComparisonAlternatives

Overview

Graylog
Graylog
Stacks595
Followers711
Votes70
GitHub Stars7.9K
Forks1.1K
Filebeat
Filebeat
Stacks133
Followers252
Votes0

Filebeat vs Graylog: What are the differences?

Introduction

Filebeat and Graylog are both tools used in the field of log management and analysis. While they serve a similar purpose, there are some key differences between the two.

  1. Scalability: One major difference between Filebeat and Graylog is their scalability. Filebeat is designed to be lightweight and efficient, making it ideal for small to medium-sized environments. It efficiently ships logs to a centralized location for further processing. On the other hand, Graylog is a more comprehensive log management solution that can handle large-scale log data ingestion and processing. It provides features like clustering and load balancing, making it suitable for enterprise-level deployments.

  2. Data processing capabilities: Filebeat is primarily a log shipper that collects log files and forwards them to a centralized location for analysis. It focuses on efficient log file shipping and does not provide extensive data processing capabilities. Graylog, on the other hand, is a powerful log management platform that not only collects logs but also offers advanced data processing features. It allows users to extract and transform log data, create custom dashboards, and run complex queries. This makes Graylog more suitable for in-depth log analysis and monitoring.

  3. User interface: Another difference is the user interface provided by each tool. Filebeat does not have a native user interface of its own. It is primarily configured and managed through command-line tools or configuration files. Graylog, on the other hand, offers a web-based user interface that provides a user-friendly and intuitive experience for log management and analysis. It allows users to easily search, filter, and visualize log data, as well as configure various settings.

  4. Alerting and notifications: Graylog provides built-in alerting and notification capabilities, which allow users to define events or conditions that trigger notifications. This feature is useful for proactive monitoring and alerting based on specific log patterns or thresholds. Filebeat, on the other hand, does not provide native alerting functionality. It is primarily focused on log shipping and does not have built-in mechanisms for alerting based on log data.

  5. Integration with other tools: Graylog is designed to integrate with a wide range of tools and systems in the log management ecosystem. It offers a variety of plugins and APIs that allow seamless integration with external systems such as Elasticsearch, Kafka, and Grafana. Filebeat, on the other hand, is more focused on log shipping and does not provide extensive integration options out of the box. However, it can be easily combined with other tools in the ELK (Elasticsearch, Logstash, Kibana) stack for more advanced log analysis.

  6. Community and support: Graylog has a larger user community and a more active development community compared to Filebeat. This means that there are more resources, documentation, and community-driven modules available for Graylog. It also ensures timely updates and support for new features and bug fixes. Filebeat, while backed by Elastic, may have a smaller community and fewer third-party resources available.

In summary, Filebeat is a lightweight log shipper that efficiently collects and forwards log files to a centralized location, while Graylog is a comprehensive log management platform that offers advanced data processing, visualization, and alerting capabilities. Graylog is more suitable for large-scale deployments and provides a user-friendly interface, extensive integration options, and a larger community support.

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Detailed Comparison

Graylog
Graylog
Filebeat
Filebeat

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.

It helps you keep the simple things simple by offering a lightweight way to forward and centralize logs and files.

Statistics
GitHub Stars
7.9K
GitHub Stars
-
GitHub Forks
1.1K
GitHub Forks
-
Stacks
595
Stacks
133
Followers
711
Followers
252
Votes
70
Votes
0
Pros & Cons
Pros
  • 19
    Open source
  • 13
    Powerfull
  • 8
    Well documented
  • 6
    Alerts
  • 5
    User authentification
Cons
  • 1
    Does not handle frozen indices at all
No community feedback yet
Integrations
GitHub
GitHub
Logstash
Logstash

What are some alternatives to Graylog, Filebeat?

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.

Sematext

Sematext

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

Fluentd

Fluentd

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.

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.

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