LogDNA vs Loggly

Overview

Loggly

Stacks269

Followers304

Votes168

LogDNA

Stacks97

Followers144

Votes18

LogDNA vs Loggly: What are the differences?

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Data Ingestion: LogDNA offers automatic parsing and indexing of log data, while Loggly allows you to define custom parsing rules for log data ingestion.
Search Capabilities: LogDNA provides a live tail feature that updates in real-time, while Loggly offers advanced search functionality through its powerful query language.
User Interface: LogDNA has a simple and user-friendly interface designed for ease of use, while Loggly provides a more complex interface with a steeper learning curve.
Alerting and Monitoring: LogDNA includes built-in alerting features for log monitoring, while Loggly offers more customizable alerting options with integration capabilities.
Cost and Pricing: LogDNA pricing is based on daily log volume, while Loggly pricing is based on data retention and features tiers.
Integration Options: LogDNA has native integrations with various platforms such as AWS, Kubernetes, and more, whereas Loggly offers a wider range of integrations with third-party tools and services.

In Summary, LogDNA and Loggly differ in data ingestion methods, search capabilities, user interface, alerting and monitoring options, cost structure, and integration possibilities.

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CLI (Node.js)

Manual

Detailed Comparison

Loggly	LogDNA
It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.	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
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	Aggregate Logs & Analyze Related Events;Easy Setup in Minutes;Powerful Search & Alerts;Save what you see as a View;Modern User Interface;Tail -f Like a Boss;Debug & Troubleshoot Faster
Statistics
Stacks 269	Stacks 97
Followers 304	Followers 144
Votes 168	Votes 18
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 6 Easy setup 4 Cheap 3 Extremely fast 2 Powerful filtering and alerting functionality 1 Multi-cloud Cons 1 Limited visualization capabilities 1 Cannot copy & paste text from visualization
Integrations
Heroku Amazon S3 New Relic AWS CloudTrail Engine Yard Cloud Cloudability	No integrations available

What are some alternatives to Loggly, LogDNA?

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.

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

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.

Related Comparisons

LogDNA vs Loggly: What are the differences?

<!-- Write Introduction here -->

Data Ingestion: LogDNA offers automatic parsing and indexing of log data, while Loggly allows you to define custom parsing rules for log data ingestion.
Search Capabilities: LogDNA provides a live tail feature that updates in real-time, while Loggly offers advanced search functionality through its powerful query language.
User Interface: LogDNA has a simple and user-friendly interface designed for ease of use, while Loggly provides a more complex interface with a steeper learning curve.
Alerting and Monitoring: LogDNA includes built-in alerting features for log monitoring, while Loggly offers more customizable alerting options with integration capabilities.
Cost and Pricing: LogDNA pricing is based on daily log volume, while Loggly pricing is based on data retention and features tiers.
Integration Options: LogDNA has native integrations with various platforms such as AWS, Kubernetes, and more, whereas Loggly offers a wider range of integrations with third-party tools and services.

In Summary, LogDNA and Loggly differ in data ingestion methods, search capabilities, user interface, alerting and monitoring options, cost structure, and integration possibilities.

LogDNA vs Loggly

Overview