Splunk vs elk LEARNOVITA

Splunk vs ELK | Differences and Which Should You Learn? [ OverView ]

Last updated on 31st Oct 2022, Artciles, Blog

About author

Pradip Mehrotra (Senior Splunk SIEM Engineer )

Pradip Mehrotra is a Sr. Splunk SIEM Engineer with 7+ years of experience, and he is a specialist in an analytics-driven SIEM tool that collects, analyzes, and correlates high volumes of network and other machine data in real-time.

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    • In this article you will learn:
    • 1.What is Splunk?
    • 2.What is ELK?
    • 3.Difference Between Splunk and ELK.
    • 4.Splunk vs ELK: Comparison.
    • 5.Conclusion.

What is Splunk?

Splunk is also termed as a “Google for log files”. All log data generated by the any device or system in an IT environment is a gathered and given as input to a Splunk. Splunk refines it and generates a powerful insight into log data through alerts, charts, graphs etc. Three key components in a Splunk are its forwarder indexer and search head. Forwarder pushed data to be remote indexer. Indexer responds to be search queries. Search head is a front end web interface where these are 3 components can be combined.

What is ELK?

ELK stands for an Elasticsearch, Logstash and Kibana. ELK consists of various software tools like a Elasticsearch (log searching tool) logstash (data router and data processing tool) and a Kibana(data visualization tool). Altogether these 3 tools are make up a full analytical tool.

Elasticsearch – a NoSQL database which uses a Lucene search engine.

Logstash – It is the transportation pipeline used to populate an Elasticsearch with data.

Kibana – It is the dashboard working on top of an Elasticsearch and provide a data analysis through visualizations and dashboards.

Difference Between Splunk and ELK:

    PropertySplunkELK
    Data Collection A Splunk Forwarder Logstash/FileBeat
    Transport Splunk TCP, HTTPS Elastic Transport, HTTPS
    Index Storage A Flat Files A Flat Files
    Indexing Technology Proprietary, C++ Bases, Schema on read Apache Lucene, Java Based, Schema on write
    Search Technology Custom MapReduce Apache Lucene
    Search Interface Splunk Search Head Kibana
    Search Language SPL(Splunk Processing Language) Apache Lucene
    Search Interface – REST API? Yes Yes
Splunk

Splunk vs ELK: Comparison:

Splunk vs ELK#1. Pricing and Support:

Splunk: Splunk is the proprietary software with a price tag. It is bit costly but has an excellent benefits. For a basic logging can always use Splunk light.

ELK: ELK is an open source so it is free.

Infrastructure Cost: Splunk and ELK both are having a similar hardware infrastructure.

Solution Implementation Cost: As a Splunk is having a price tag attached to it it comes with the some consulting hours to implement the solution. Whereas for an ELK need to pay extra for a same.

Maintenance Cost: In Splunk support hours are also included are while purchasing. But in an ELK don’t have any support. So need to pay some extra bucks for a professional services.

Plugins and Add-ons Cost: To extend functionalities Splunk and ELK both the support plugin/add-on based solutions. Few of them can be a free and few can be an expensive.

Splunk vs ELK#2. Features and Implementation:

Loading Data:

Splunk can accept any data in the any format i.e. csv or json or be any other log format. In case of an ELK logstash is responsible for a data processing. Logstash doesn’t support all data types. Plugins are required to work with data types in logstash. But with logstash it is complex to debug with errors as it uses a non-standard configuration language. Moreover for ELK need to identify and configure a data fields before injecting into system. Whereas for a Splunk and can inject the data as it is and as it comes with the some pre-configurations. Also in case of a GUI also splunk has an upper-hand over an ELK due to its user friendly and intuitive nature.

Visualizations:

  • Splunk UI has a flexible controls to edit and add new components to the dashboards. It also allows various customized view for different users by configuring dashboards controls the differently for them. Along with all these features it also supports a visualizations on a mobile device having a Splunk application.
  • ELK has Kibana tool for the visualizations. Kibana has all features to build the dashboards pretty quickly using its own built-in aggregators. But one thing need to make sure is a data types. If they are incorrect, aggregator functions not work. Filtering data is more easier and advanced in ELK stack. Although a Kibana doesn’t provide a user management can have this functionality by using out of a box ELK hosted solutions.

Splunk vs ELK#3. Release rate of new updates.

  • Both the software tools provide periodic updates by a fixing bugs and enhancing their software with a new features. Splunk is always available right now with 7.1 version whereas an ELK is available at a 6.4 version.
  • Splunk is generally having the quarterly release cycle. On the other side, ELK releases a new updates much faster than a prior. This arises questions in a mind to think about a quality of ELK’s build releases.

Splunk vs ELK#4. Companies who work with these tools:

There are more hi-fi companies using a Splunk for log management. Splunk is offering their services to an approximately 12000 customers. 89 amongst them are in a Fortune 100 list.

Splunk vs ELK#5. API and Extensibility:

  • Splunk offer a RESTful API with over 200 endpoints to access each and every feature residing in a product. Also this API is well-documented which makes a work easier and faster. It also provide a product SDKs for more popular languages.
  • ELK Stack has a Elasticsearch which was designed as distributed search and analytics engine using a standard RESTful APIs and JSON. ELK offers pre-built clients for creating a customized apps in various languages like a Python Java .NET and more.
ELK

Splunk vs ELK#6. Integration and Plugins:

Splunk was proved to be a better when it comes to set-up an integrations with other tools. Splunk provides almost 1000 add-ons and apps which are divided into the 6 different categories:

  • IoT/industrial data.
  • IT operations.
  • DevOps.
  • Utilities.
  • Business analytics.
  • Security/fraud/compliance.

Conclusion:

Although Splunk and ELK are the great tools for log management a choice for the any tools must depend on a customer’s specific needs infrastructure size and cost. For any small or medium enterprise having a low budget should go for ELK while a large enterprise should choose Splunk over a ELK.

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