Log management solutions play a pivotal role in an organization’s security framework. Without these solutions, enterprise can face security comprises or data breaches due to low visibility of actions and events happening in the infrastructure. The tools available for logging are in abundance. How can you choose the appropriate tool? Which is the best amongst the leading two log management tools solutions - Splunk or ELK (Elastic Stack)? Let’s stack up their comparison between Splunk vs ELK to choose the best tool.
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In this Splunk vs ELK article, we will go through below topics
So let us get started with this Splunk vs ELK article,
Splunk is also termed as “Google for log files”. All the log data generated by any device or system in an IT environment is gathered and given as input to Splunk. Splunk refines it and generates powerful insight into the log data through alerts, charts, graphs etc.
Three key components in Splunk are its forwarder, indexer and search head. Forwarder pushed data to remote indexer. Indexer responds to search queries. Search head is the front end web interface where these 3 components can be combined.
ELK stands for Elasticsearch, Logstash, and Kibana. ELK consists of different software tools like Elasticsearch (log searching tool), logstash (data router and data processing tool) and Kibana(data visualization tool). Altogether, these 3 tools make up a full analytical tool.
[Related Page: Elasticsearch Tutorial]
Let us summarize all the technical information we learned in below table.
|Data Collection||Splunk Forwarder||Logstash/FileBeat|
|Transport||Splunk TCP, HTTPS||Elastic Transport, HTTPS|
|Index Storage||Flat Files||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 is a proprietary software with a price tag. It is a bit costly but has excellent benefits. For basic logging, you can always use Splunk light.
[Related Page: Splunk Logging]
ELK: ELK is open source, so it is free.
But to own a software, you need to consider many other costs along with software cost. Below are few costs which you should keep in mind while owning any software.
[Related Page: Elasticsearch Installation]
Splunk can accept any data in any format i.e. csv or json or any other log format. In case of ELK, logstash is responsible for data processing. Logstash doesn’t support all the data types. Plugins are required to work with those data types in logstash. But with logstash, it is difficult to debug with errors as it uses non-standard configuration language.
Moreover for ELK, we need to identify and configure data fields before injecting into system. Whereas for Splunk, we can inject the data as it is and as it comes with some pre-configurations. Also in case of GUI also, splunk has an upper-hand over ELK due to its user friendly and intuitive nature.
Splunk UI has flexible controls to edit and add new components to your dashboards. It also allows different customized view for different users by configuring dashboards controls differently for them. Along with all these features, it also supports visualizations on a mobile device having Splunk application.
ELK has Kibana tool for visualizations. Kibana has all the features to build the dashboards pretty quickly using its own built-in aggregators. But one thing we need to make sure is the data types. If they are incorrect, aggregator functions won’t work. Filtering data is much easier and advanced in ELK stack. Although Kibana doesn’t provide user management, we can have this functionality by using out of the box ELK hosted solutions.
For any log management software, search capabilities is the most important feature. Splunk uses its own Splunk Search Processing Language (SPL) to make search queries. Whereas ELK uses Lucene query language for search queries.
Lucene is similar with other scripting languages so it will be easy to learn. In case of SPL, it is proprietary and needs to be learnt to work on it. The key difference between SPL and Lucene is SPL supports search pipeline which Lucene doesn’t support. Search pipeline is one command’s output is input for the next one. Lucene is straightforward and used to generate output of one command without any transformations.
Both software tools provide periodic updates by fixing bugs and enhancing their software with new features. Splunk is available right now with 7.1 version whereas ELK is available at 6.4 version.
Splunk is generally having a quarterly release cycle. On the other side, ELK releases their new updates much faster than prior. This arises questions in my mind to think about the quality of ELK’s build releases.
[Related Page: Splunk Software]
There are very hi-fi companies using Splunk for their log management. Splunk is offering their services to approximately 12000 customers. 89 amongst them are in Fortune 100 list. Below are few companies using Splunk.
ELK is also having same impressive companies list. Below are the top customers served by ELK.
Splunk has a great customer base so its community is also large. On those communities, you will be able to find all your answers. Furthermore, Splunk is also having a developer community. So a Splunk licence can give you access to these communities as well as their enterprise support.
ELK is an open source software. But they offer paid support. So it is a “freemium” model of software. There are so many open source communities for ELK which provides support and answers to your questions. But there is a drawback of data confidentiality/security.
Splunk provide a RESTful API with over 200 endpoints to access each and every feature residing in the product. Also this API is well-documented which makes the work easier and faster. It also offers product SDKs for many popular languages.
ELK Stack has Elasticsearch which was designed as a distributed search and analytics engine using standard RESTful APIs and JSON. ELK offers pre-built clients for creating customized apps in various languages like Python, Java, .NET and more.
Splunk was proved to be better when it comes to set-up the integrations with other tools. Splunk offers almost 1000 add-ons and apps which are divided into 6 different categories:
Although ELK also supports plethora of plugins. But it doesn’t have much integrations like Splunk. Logstash responsible for data loading is only having 160 integrations as of now.
Learning curve for both tools are steep. As for both the products we need knowledge about Regex, scripting languages and TCP/IP. But compared to Splunk, ELK’s curve is flat as there are lots of materials available online due to ELK being an open source platform. Splunk offers trial period with its extensive and useful documentation. Although, its advances courses are pricy.
Below is the summarized table comparing features between Splunk and ELK.
|Inject any data type||?||Plug in Needed|
|Documentation and Community||?||?|
|Plugins and Integration||?||?|
Although Splunk and ELK are great tools for log management, a choice for any tools must depend on customer’s specific needs, infrastructure size and cost. For any small or medium enterprise having low budget should go for ELK while a large enterprise should choose Splunk over ELK.
If Splunk interests you, then go and check out our Splunk online training which comes with lifetime access to videos and training materials.