Introduction to Splunk Vs. ELK

Blog > Introduction to Splunk Vs. ELK

Here we will discuss and compare the benefits of “Splunk Vs. ELK,” including their integration. Here we analyze the efficiency of Splunk and ELK for all sizes of businesses.

Splunk Vs. ELK

ELK

• Elasticsearch is a search server
• Three parts that make ELK.
  • Elasticsearch; provides the storage and analytics engine
  • Logstash; provides the collection and transformation agent
  • Kibana; provides visualization of data

• Built on Java
• Shield; for encryption and authentication

Splunk Enterprise

Splunk also captures indexes and correlates real-time data in a searchable repository from which the user can generate graphs, reports alerts, dashboards, and other visualizations. It helps to produce valuable business insights among the machine data types. Splunk can analyze application logs file system, Audit logs, SCADA data, and web access logs. It uses Search Processing Language (SPL); it’s a decomposed JSON format.

 

Category	Splunk	ELK Stack
Features	Splunk has a search capability, Reporting, Alerts, and data visualization.	Search capability, Reporting, Alerts, and data visualization.
Setup and Maintenance	Easy	Bit challenging
Solution	On-Perm and SaaS	On-Perm and SaaS
API & Extensibility	Two hundred plus API	Provides API support
Plugin Support	Yes	Yes
Components	Forwarder, indexer, and search head	Logstash, Elasticsearch, and Kibana
Search	SPL	Query DSL
Compression	Yes	No
Customer Support	Proficient	Good
Community Support	Good Community Support	Better than Splunk

 

Splunk Vs. ELK

ELK	Splunk
ELK is an open-source tool.	Splunk is a commercial tool.
ELK stack does not offer Solaris portability because of Kibana.	Splunk offers Solaris portability
Processing speed is strictly limited	Offers accurate and speedy processes
ELK technology stack created with the combination of ElasticSearch-Logstash-Kibana	Splunk is a proprietary tool. It provides both on-premise and cloud solutions.
In ELK, searching analysis and visualization will only be possible after the ELK stack setup.	Splunk is a complete data managing package at user’s disposal.
ELK is not supporting integration with other tools.	Splunk is a useful tool for setting up integration with other tools.

Splunk Pros & Cons

Pros	Cons
Splunk provides a clean, intuitive user interface.	Splunk can be expensive
The user can connect Splunk to almost any machine data source.	Requires learning SPL
Flexibility and the ability to conduct fast searches over large data volumes.	Does not support no-code experience
Easy to deploy and provides highly customizable solutions for enterprises that require fast search over large data volumes.	Time taking integration
Splunk is on a security analytics mission; most enterprises use Splunk in some capacity for infrastructure monitoring application analytics or security. For security, Splunk is building its future around its cloud-based unified security platform.	Splunk has been slower to the cloud than others in this evaluation and cloud-native newcomers to the security analytics market.

 

ELK Stack Pros & Cons

Pros	Cons
ELK stack offers incredible scalability with a massively distributed structure.	Tuning for ingress performance can be tricky.
Elasticsearch clusters can detect failed nodes to organize and distribute data automatically.	The documentation could be a bit more detailed and have more examples, especially for advanced functionality.
Elastic stack offers full-text searching capabilities with a query API that supports multilingual search geolocation, contextual suggestions, auto-complete, and result snippets.	The ingest pipeline structure is more complicated and confusing than previous implementations for using things like attachment plugins.
It has a very powerful aggregation engine that can allow for tons of customizable analytics and reports.	Complex query mechanism and architecture to set up and optimize.
Elasticsearch has a new Elastic Cloud SaaS solution which is very easy to deploy, set up, and scale with all features and more.	The user interface is heavy in Java requirements, and sometimes the user can get some lag displaying heavy results for heavy queries.

 

Author: SVCIT Editorial Copyright
Silicon Valley Cloud IT, LLC.