Splunk Vs Elk: Which One Should You Choose?

Anyone who is in IT Operations must have heard and even worked with Splunk or ELK, two of the most widely used tools in the domain of Operational Data Analytics. Both Spunk and ELK share a common aim, that is, to solve Log Management issues and make it more seamless.

Log Management solutions such as Spunk and ELK are crucial to an organization’s layered security framework. Without them, companies would hardly have any visibility into the actions and events occurring inside their infrastructures that could be a source of vulnerability (data breaches or a breach in security).

In the face of the ever-growing log data of IT companies, Spunk and ELK seek to manage the expanding log data while offering a scalable approach to collect and index log files and provide a search interface to interact with data. Apart from this, both these nifty tools allow users to secure the collected data and also to create visualizations (reports, dashboards, and alerts) for the same.

Although both these tools are designed to serve the same purpose, the difference between Splunk and ELK cannot be ignored! In fact, the Splunk vs. ELK debate is a long-standing debate in the industry. In this post, we’ll dig deeper into the difference between Splunk and ELK and see how they compare to each other in various aspects. But first, let’s learn a little about them separately.


With Splunk, users can unify log file data collected from diverse systems and devices across an IT environment and perform higher-order security analyses and assessments to determine the collective state of the company’s systems from a unified interface. Splunk uses a proprietary search language — Search Processing Language (SPL) — for serving and executing contextual queries in large data sets.

It also boasts of over 1000 apps and add-ons designed to extend its capabilities to accommodate disparate data sources.


Splunk vs ELK

1. Technology

While both Splunk and ELK store data in Indexes, Splunk uses a proprietary technology (primarily developed in C++) for indexing, and ELK leverages Apache Lucene, an open-source technology written in Java. Furthermore, for search purposes, Splunk uses a Search Head (a Splunk instance with specific functions for searching), whereas ELK uses Kibana, an open-source data visualization platform.

Querying in Splunk is done by using its proprietary SPL (Splunk Processing Language whose syntax resembles SQL-like statements with Unix Pipe), ELK employs Query DSL with an underlying JSON formatted syntax.

2. Visualizations

For visualization, ELK has Kibana in the ELK Stack. Just like Splunk Web UI, Kibana also allows you to create visualizations like line charts, tables, etc., and present them on the dashboard. There’s also a search filter that appears above the different views. So, if you use a query, it will be automatically applied to elements of the dashboard. However, unlike Splunk, Kibana does not support user management (for this, you can use hosted ELK solutions that offer it out-of-the-box).

3. Cost

For instance, if you buy a 1TB license from Splunk, you can consume up to 1TB per day. However, keep in mind that there’s no cost of keeping the historical data — only the daily volume is counted, and the License Meter resets every day at midnight. Also, the price does not vary for the number of users or CPU cores. (if any).

4. Ease of Use

5. API and Extensibility

6. Learning Curve

Wrapping Up



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