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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Fluentd vs Loggly

Fluentd vs Loggly

OverviewComparisonAlternatives

Overview

Loggly
Loggly
Stacks269
Followers304
Votes168
Fluentd
Fluentd
Stacks630
Followers688
Votes39
GitHub Stars13.4K
Forks1.4K

Fluentd vs Loggly: What are the differences?

# Introduction

Key differences between Fluentd and Loggly are outlined below:

1. **Architecture**: Fluentd is an open-source data collector that unifies the data collection and consumption process. It has a plugin-based architecture that allows for easy customization and integration with various data sources. On the other hand, Loggly is a cloud-based log management service that centralizes log data for easy analysis and monitoring. It utilizes a proprietary architecture optimized for log data storage and retrieval.

2. **Scalability**: Fluentd is known for its ability to handle large volumes of data efficiently. It supports horizontal scaling by distributing data collection tasks across multiple nodes. In contrast, Loggly provides a scalable log management solution but is limited by the resources allocated in the cloud platform where it is hosted. It may require additional configuration or resources to handle sudden spikes in log data.

3. **Flexibility**: Fluentd offers flexibility in terms of data processing and routing. It supports various output plugins for sending data to different destinations, such as databases, storage services, and data warehouses. Loggly, while flexible in terms of log ingestion and search capabilities, may have limitations in terms of data export options or integrations with external systems.

4. **Cost**: Fluentd is an open-source project that can be deployed on-premises or in the cloud at minimal cost. Organizations have the option to manage and scale their Fluentd deployment based on their requirements. On the contrary, Loggly is a subscription-based service that requires a monthly or annual fee based on the volume of log data ingested and features utilized. This ongoing cost may become a factor for organizations with budget constraints.

5. **Search and Analysis Capabilities**: Fluentd primarily focuses on data collection and transport, leaving the analysis and visualization tasks to downstream tools. In comparison, Loggly includes built-in search and analysis features, such as real-time log monitoring, trend analysis, and alerting. This can be advantageous for organizations looking for a comprehensive log management solution with integrated analytics capabilities.

6. **Community Support and Documentation**: Fluentd has a vibrant open-source community that actively contributes plugins, extensions, and resources to support users. The documentation for Fluentd is extensive and regularly updated, making it easy for users to find solutions to common issues. In contrast, Loggly's support and documentation are primarily provided through its commercial offerings, which may result in limited community-driven resources and solutions.

In Summary, the key differences between Fluentd and Loggly lie in their architecture, scalability, flexibility, cost structure, search and analysis capabilities, and community support and documentation. Each solution brings its strengths and limitations to the table, catering to different needs in log management and data collection.

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Detailed Comparison

Loggly
Loggly
Fluentd
Fluentd

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

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.

See what your application is doing during development;Catch exceptions and track execution flow;Graph and report on the number of errors generated;Search across multiple deployments;Narrow down on specific issues;Investigate root cause analysis;Monitor for specific events and errors;Trigger alerts based on occurrences and investigate for resolutions;Track site traffic and capacity;Measure application performance;A rich set of RESTful APIs which make data from applications easy to query;Supports oAuth authentication for third-party applications development (View our Chrome Extension with NewRelic);Developer ecosystem provides libraries for Ruby, JavaScript, Python, PHP, .NET and more
Open source; Flexible; Minimum resources; Reliable
Statistics
GitHub Stars
-
GitHub Stars
13.4K
GitHub Forks
-
GitHub Forks
1.4K
Stacks
269
Stacks
630
Followers
304
Followers
688
Votes
168
Votes
39
Pros & Cons
Pros
  • 37
    Centralized log management
  • 25
    Easy to setup
  • 21
    Great filtering
  • 16
    Live logging
  • 15
    Json log support
Cons
  • 3
    Pricey after free plan
Pros
  • 11
    Open-source
  • 10
    Great for Kubernetes node container log forwarding
  • 9
    Easy
  • 9
    Lightweight
Integrations
Heroku
Heroku
Amazon S3
Amazon S3
New Relic
New Relic
AWS CloudTrail
AWS CloudTrail
Engine Yard Cloud
Engine Yard Cloud
Cloudability
Cloudability
No integrations available

What are some alternatives to Loggly, 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.

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.

LogDNA

LogDNA

The easiest log management system you will ever use! LogDNA is a cloud-based log management system that allows engineering and devops to aggregate all system and application logs into one efficient platform. Save, store, tail and search app

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