Loggly vs Logstash

Overview

Loggly

Stacks269

Followers304

Votes168

Logstash

Stacks12.3K

Followers8.8K

Votes103

GitHub Stars14.7K

Forks3.5K

Loggly vs Logstash: What are the differences?

Architecture: Loggly is a cloud-based log management solution, whereas Logstash is an open-source data collection engine that collects and processes log data.
Setup and Maintenance: Loggly requires no setup or maintenance as it is a SaaS solution, while Logstash needs to be installed, configured, and maintained by the user.
Scalability: Loggly offers automatic scaling and resources management, making it easy to handle large volumes of log data, whereas Logstash scalability can be challenging and requires manual effort for optimization.
Integration: Loggly integrates seamlessly with various platforms and tools, providing a wide range of plugins and configurations, while Logstash might require custom scripts or configurations for specific integrations.
Support and Community: Loggly provides dedicated customer support, documentation, and community forums, ensuring prompt assistance and resources for users, whereas Logstash relies more on community support and may have limited official support options.
Cost: Loggly follows a subscription-based pricing model, which may be more predictable and cost-effective for organizations, while Logstash is free to use but may involve hidden costs related to setup, maintenance, and scalability.

In Summary, Loggly and Logstash differ in architecture, setup, scalability, integration, support, and cost, making them suitable for different use cases and preferences.

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Manual

Detailed Comparison

Loggly	Logstash
It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.	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.
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	Centralize data processing of all types;Normalize varying schema and formats;Quickly extend to custom log formats;Easily add plugins for custom data source
Statistics
GitHub Stars -	GitHub Stars 14.7K
GitHub Forks -	GitHub Forks 3.5K
Stacks 269	Stacks 12.3K
Followers 304	Followers 8.8K
Votes 168	Votes 103
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 69 Free 18 Easy but powerful filtering 12 Scalable 2 Kibana provides machine learning based analytics to log 1 Well Documented Cons 4 Memory-intensive 1 Documentation difficult to use
Integrations
Heroku Amazon S3 New Relic AWS CloudTrail Engine Yard Cloud Cloudability	Kibana Elasticsearch Beats

What are some alternatives to Loggly, Logstash?

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

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 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.

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

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

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

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

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

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

Related Comparisons

Loggly vs Logstash: What are the differences?

Architecture: Loggly is a cloud-based log management solution, whereas Logstash is an open-source data collection engine that collects and processes log data.
Setup and Maintenance: Loggly requires no setup or maintenance as it is a SaaS solution, while Logstash needs to be installed, configured, and maintained by the user.
Scalability: Loggly offers automatic scaling and resources management, making it easy to handle large volumes of log data, whereas Logstash scalability can be challenging and requires manual effort for optimization.
Integration: Loggly integrates seamlessly with various platforms and tools, providing a wide range of plugins and configurations, while Logstash might require custom scripts or configurations for specific integrations.
Support and Community: Loggly provides dedicated customer support, documentation, and community forums, ensuring prompt assistance and resources for users, whereas Logstash relies more on community support and may have limited official support options.
Cost: Loggly follows a subscription-based pricing model, which may be more predictable and cost-effective for organizations, while Logstash is free to use but may involve hidden costs related to setup, maintenance, and scalability.

In Summary, Loggly and Logstash differ in architecture, setup, scalability, integration, support, and cost, making them suitable for different use cases and preferences.

Loggly vs Logstash

Overview