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

Graylog vs Loggly

OverviewComparisonAlternatives

Overview

Loggly
Loggly
Stacks269
Followers304
Votes168
Graylog
Graylog
Stacks595
Followers711
Votes70
GitHub Stars7.9K
Forks1.1K

Graylog vs Loggly: What are the differences?

Introduction

Graylog and Loggly are both popular log management solutions used for aggregating, analyzing, and storing log data. While they serve similar purposes, there are key differences between the two platforms.

  1. Integration Flexibility: Graylog offers more flexibility in terms of integrating with various sources. It supports a wide range of log collecters such as Elasticsearch, Beats, NXLog, and more. On the other hand, Loggly has limited integrations with a smaller set of log collectors.

  2. Deployment Options: Graylog provides both cloud-based and on-premises deployment options. This allows users to choose the most suitable option based on their preferences and requirements. Loggly, on the other hand, is primarily a cloud-based log management solution, which may not be suitable for organizations with strict compliance requirements or those preferring on-premises deployments.

  3. Query Language: Graylog utilizes a powerful query language called Graylog Query Language (GQL), which allows users to perform complex searches, create custom dashboards, and build visualizations. Loggly, on the other hand, uses a simplified query syntax based on Apache Lucene, which may not offer the same level of query flexibility and customization.

  4. Data Retention: Graylog provides more flexible data retention options, allowing users to define their own retention policies based on their specific needs. Loggly, on the other hand, has predefined retention periods based on the plan chosen, which may not align with the varying retention requirements of different organizations.

  5. Alerting Capabilities: Graylog offers advanced alerting features, allowing users to configure custom alert conditions and notifications based on log data. Loggly also supports alerting, but it has more limited options and may not provide the same level of granularity as Graylog.

  6. User Interface: Graylog provides a comprehensive and customizable user interface, giving users more control over how they interact with the log data. Loggly, on the other hand, has a simpler interface with less customization options, which may be more suitable for users looking for a streamlined logging experience.

In summary, Graylog offers more integration flexibility, deployment options, query capabilities, data retention options, advanced alerting features, and a comprehensive user interface compared to Loggly. However, Loggly may be a suitable choice for users looking for a simpler, cloud-based log management solution.

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Detailed Comparison

Loggly
Loggly
Graylog
Graylog

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

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.

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
-
Statistics
GitHub Stars
-
GitHub Stars
7.9K
GitHub Forks
-
GitHub Forks
1.1K
Stacks
269
Stacks
595
Followers
304
Followers
711
Votes
168
Votes
70
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
  • 19
    Open source
  • 13
    Powerfull
  • 8
    Well documented
  • 6
    Alerts
  • 5
    User authentification
Cons
  • 1
    Does not handle frozen indices at all
Integrations
Heroku
Heroku
Amazon S3
Amazon S3
New Relic
New Relic
AWS CloudTrail
AWS CloudTrail
Engine Yard Cloud
Engine Yard Cloud
Cloudability
Cloudability
GitHub
GitHub

What are some alternatives to Loggly, Graylog?

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.

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.

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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