Loggly vs Scalyr

Last updated: January 08, 2018

11
Loggly
Solve Operational Problems Faster. Make all of your logs accessible to everyone in one place. No more logging into individual machines. Use searches, filters and graphs to spot trends and narrow down potential root causes. Set up in minutes. No software or agents to install. Works with all standard logging facilities. Owned by SolarWinds.
5
Scalyr
Server Log Monitoring Tool. We built the log monitoring tool we've always wished for. Scalyr is server log monitoring and analysis built for engineers. Turn chaotic logs and system metrics into actionable data.
Loggly vs Scalyr in our news:

2018. SolarWinds acquires log-monitoring service Loggly



IT management company SolarWinds has acquired the cloud-based log-monitoring and analytics service Loggly. According to its marketing materials, about a third of the Fortune 500 use the company’s services, including the likes of Lenovo, Pizza Hut and Dell. SolarWinds argues that this acquisition will expand the company’s engineering and analytics expertise and that it will push the company’s overall strategy of building a full-stack monitoring platform. SolarWinds, which has acquired its fair share of companies (including Pingdom) over the years, will keep the Loggly brand and product alive.


2015. Server log monitoring tool Scalyr raises $2.1M



Scalyr, a log-monitoring service that gives developers more insight into how their applications are performing, has raised a $2.1 million seed round. The idea behind Scalyr, then, is to get all data from server logs, as well as various metrics, error reports and other performance data and run it through a single tool that you can get actionable data from. Services like Splunk and Loggly offer similar log management services, but those tools make it easy to see anecdotes and it’s hard to roll that up into an overview. Scalyr also doesn’t see New Relic as a competitor either because that company’s focus tends to be on performance, while Scalyr focuses more on errors. Log files can quickly grow very large, and analyzing them takes quite a bit of compute power. The team built a new data management engine for its service to handle all of this data.