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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. ELK vs Logstash

ELK vs Logstash

OverviewComparisonAlternatives

Overview

Logstash
Logstash
Stacks12.3K
Followers8.8K
Votes103
GitHub Stars14.7K
Forks3.5K
ELK
ELK
Stacks863
Followers941
Votes23

ELK vs Logstash: What are the differences?

Developers describe ELK as "The acronym for three open source projects: Elasticsearch, Logstash, and Kibana". 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. On the other hand, Logstash is detailed as "Collect, Parse, & Enrich Data". 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.

ELK and Logstash can be primarily classified as "Log Management" tools.

Logstash is an open source tool with 10.3K GitHub stars and 2.78K GitHub forks. Here's a link to Logstash's open source repository on GitHub.

Airbnb, reddit, and Typeform are some of the popular companies that use Logstash, whereas ELK is used by Troopers, VCCloud, and home24. Logstash has a broader approval, being mentioned in 563 company stacks & 278 developers stacks; compared to ELK, which is listed in 53 company stacks and 14 developer stacks.

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Detailed Comparison

Logstash
Logstash
ELK
ELK

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.

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.

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
14.7K
GitHub Stars
-
GitHub Forks
3.5K
GitHub Forks
-
Stacks
12.3K
Stacks
863
Followers
8.8K
Followers
941
Votes
103
Votes
23
Pros & Cons
Pros
  • 69
    Free
  • 18
    Easy but powerful filtering
  • 12
    Scalable
  • 2
    Kibana provides machine learning based analytics to log
  • 1
    Great to meet GDPR goals
Cons
  • 4
    Memory-intensive
  • 1
    Documentation difficult to use
Pros
  • 14
    Open source
  • 4
    Can run locally
  • 3
    Good for startups with monetary limitations
  • 1
    Easy to setup
  • 1
    External Network Goes Down You Aren't Without Logging
Cons
  • 5
    Elastic Search is a resource hog
  • 3
    Logstash configuration is a pain
  • 1
    Bad for startups with personal limitations
Integrations
Kibana
Kibana
Elasticsearch
Elasticsearch
Beats
Beats
No integrations available

What are some alternatives to Logstash, ELK?

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.

Loggly

Loggly

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

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.

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.

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.

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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