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Splunk Vs Elk: Which One Should You Choose? [Complete Comparison]

Splunk Vs Elk: Which One Should You Choose? [Complete Comparison]

Q: 1. Why should anyone learn Splunk?

The first thing that comes to mind when studying Big Data is either R or Python. Splunk, however, is the most widely used tool to work with data generated through machines. Businesses nowadays are using Splunk, since it is the industry-standard tool for operation. As companies will continue to leverage the benefit of Big Data, so will there be an increase in Splunk’s popularity. Once enough understanding is gained of subjects like architecture, Big Data, etc., the opportunities for Splunk will automatically grow. Splunk is one of the most popular platforms that are effective for managing machine-generated data and working flexibly with them. All these factors make Splunk one of the most efficient tools to be learned about.

Q: 2. What are the advantages of Elk?

Elasticsearch or Elk is scalable. It is comfortable to operate on any machine. The various aspects of scalability include throughput, index size, and cluster size. Secondly, Elk is also brilliant with its performance. It uses large data sets and finds relevant searches based on those sets. With the help of the completion suggestion, the autocomplete functionality takes a turn and is also an effective feature of Big Elk. Elasticsearch is a real-time search platform that allows quick indexing of documents and provides magnificent results. Elk is schema-free which is one of the best benefits of working with Big Elk. One can avoid using the indexing process and index files at ease.

Q: 3. How can Splunk assist in career growth?

The last few years have been magnificent for Big Data and IoT, and as a lucrative career option, there are plenty of job titles to work with which include, technical service manager, security manager, software manager, programming analyst, and systems engineer. The paychecks for all these jobs and positions are extremely enticing. With Splunk, one gets the wings to fly higher and attain greater heights in the data management career. Compared to other IT roles, the salary, and the job is very exciting to establish a career in the field.

By Kechit Goyal

Updated on Nov 10, 2022 | 7 min read | 11.0k views

Table of Contents

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.

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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.

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Splunk

Splunk is so popular in the industry that it has come to be known as the “Google for log files.” Splunk is one of the top DevOps tool in the market. Apart from being a log management and analysis solution, Splunk is also a Security Information and Event Management (SIEM) solution.

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 large data sets.

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

ELK

ELK is the short form of Elasticsearch, Logstash, and Kibana. Offered by software company Elastic, ELK is an open-source, consolidated data analytics platform. ELK’s software stack comprises of Elasticsearch (distributed RESTful search/analytics engine), Logstash (a data processing pipeline), and Kibana (for data visualization). Only recently did Beats (agent-based, single-purpose data shipping) join the stack.

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Splunk vs. ELK

Let’s break down the differences between Splunk and ELK into six components:

1. Technology

Essentially, Splunk is a single closed-source product, whereas ELK combines the power of three open-source products – ElasticSearch, LogStash, and Kibana. Although both Splunk and ELK use an Agent to collect the log file data from the target servers, in Splunk, the Splunk Universal Forwarder is the Agent, and in ELK, LogStash functions as the Agent.

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.

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2. Visualizations

The Splunk Web UI is equipped with flexible controls that let you edit and add new components to your dashboard. You can configure the management and user controls for multiple users where each user can have a customized dashboard. Another great aspect of Splunk is that it supports visualizations on mobile devices as well. Even on mobile devices, you can customize the application and visualization components using XML.

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

When it comes to cost, ELK is open-source, meaning it is free. You can use ELK free of cost. Splunk, however, comes with a price. You can get a Term license for which you have to pay per year, or you could get a perpetual license, which is just a one-time fee plus annual support fee. Splunk’s license fee is based on the Daily Log Volume that is indexed.

For instance, if you buy a 1TB license from Splunk, so 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

Even though both Spunk and ELK are relatively easy to deploy and use, Splunk’s dashboards incorporate much more accessible features than ELK’s. Also, the configuration options of Splunk are a tad refined and more intuitive than that of ELK. Furthermore, many users may find ELK’s user management features to be more challenging to use than Splunk’s.

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5. API and Extensibility

Splunk has a well-documented RESTful API that contains more than 200 endpoints for accessing various features in Splunk, including SDKs in the most popular languages. Contrary to this, ELK’s Elasticsearch is a distributed search and analytics engine that leverages the standard RESTful API and JSON. However, like Splunk, it also provides many pre-built options for building custom apps in popular languages like Python, Java, .NET, to name a few.

6. Learning Curve

ELK Stack has a flat learning curve. Since ELK offers paid courses (not too expensive) that help you understand the nitty-gritty of the solution, it becomes easier to master ELK. Plus, ELK is an open-source platform, which means that there are always plenty of free learning resources online. As for Splunk, it has a moderate learning curve. Although Splunk offers a trial period with extensive documentation, if you wish to go for the advanced Splunk courses, you will have to shell out a substantial amount of money.

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Wrapping Up

To conclude, both Splunk and ELK are excellent solutions. Each has its unique advantages and limitations, and hence, the benefits of these two tools largely depend on user-specific needs and requirements. Although at present, Splunk can boast of a much more extensive offering base, remember that ELK is open-source. So, new additions are being made to it even as we speak.