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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.
Pros of ELK
- Open source14
- Can run locally4
- Good for startups with monetary limitations3
- External Network Goes Down You Aren't Without Logging1
- Easy to setup1
- Json log supprt0
- Live logging0
Pros of Logstash
- Free69
- Easy but powerful filtering18
- Scalable12
- Kibana provides machine learning based analytics to log2
- Great to meet GDPR goals1
- Well Documented1
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Cons of ELK
- Elastic Search is a resource hog5
- Logstash configuration is a pain3
- Bad for startups with personal limitations1
Cons of Logstash
- Memory-intensive4
- Documentation difficult to use1