Differences Between Splunk vs Elastic Search
When we are talking about Log Management solutions the first question comes to mind — Is Splunk better than Elastic Search or vice-a-versa?
Log Management solutions — The Need
Log management tools play a vital role in an enterprise’s layered security —without them, companies have very little visibility into the actions and events occurring inside their technology infrastructures that could either lead to data breaches or signify a security compromise in progress. Splunk and Elastic Search are two of the leading enterprise competitors in this category. Which tool you use depends on what are you trying to capture and alert your people on, and whether you are going to fork some open-source application on GitHub or buy some commercial software from vendors; let’s see how they stack up in this comparison.
Head to Head Comparison Between Splunk and Elastic Search (Infographics)
Below is the top 5 Differences Between Splunk and Elastic Search:
Key Differences Between Splunk and Elastic Search
Below are the lists of points that describe the key differences between Splunk and Elastic Search:
-
Splunk vs Elastic Search — The Basics
Splunk inherited the long-term solution of the BIG-DATA problem way before it existed in the market in 2003 when Michael Baum, Rob Das, and Erik Swan came up with the solution of capturing data logging and machine data logs to confirm the integrity of the systems that time. On the other hand, Elastic Search was founded by Shay Banon in 2010 when the BIG-DATA problem existed and people wanted some other logging and monitoring tools to test and compare Splunk’s performance and then a company was founded around it, called as Elastic.
The biggest problem with Splunk was and still is that it is an expensive and paid tool on the other side of the river Elastic Search is free and an open-source solution
4.5 (8,105 ratings)
View Course
Conclusion: Splunk and Elastic Search both are the most comprehensive and customizable solutions but one being expensive and others being open-source.
-
Splunk vs Elastic Search — The Target Problem and Solution
Splunk has traditionally served the big enterprise clients in the past which are opting out for an on-premises solution because of the data integrity issues and now they are trying to capture the smaller companies as their clients by making their services affordable. Elastic Search, on the other hand, tends to provide end to end open source and some premium services for all kinds of companies out there in this domain. With there on-cloud consumed and data Retention components they are very famous amongst the newbies and start-ups. They also tend to serve their clients with specific use case solution which are generic in nature.
If you are looking for dynamic greps and good visualizations then Elastic search + Kibana is the one for you and if your use cases are frequently changing one with every release and deployment then you should definitely try out Splunk.
Conclusion: Patiently analyze your use case and then decide which one to opt-out for.
-
Splunk vs Elastic Search — The Set-Ups
Splunk has distributed their services around two modules Splunk Enterprise targets the on-prem specializations and Splunk Cloud tries to serve the cloud-based specializations through the web app as both has comparatively similar features. The daily limits of usage are the things that are on the table for bargains with both the services.
On the other hand, Elastic Search has only one SaaS platform which has a paid module for deployment rest other modules are free and open-source which are really very helpful for small companies to monitor their enterprise logs without paying any money for their own data.
Conclusion: If you have decided to go with the Elastic Search then be ready to put some extra efforts as the success of Elastic Search depends on your own efforts but If you want to have an easy and viable solution then be ready to lose some money out of your pockets.
-
Splunk vs Elastic Search — The UI and Dashboards Visualizations
Nowadays, people are very much into the user interface and other visualization stuff and eventually, people are expecting very much out of the black log screens.
Eventually, Splunk has improved its user interface with new dashboard controls, good and interacting graphical interfaces and abilities to assign the tasks and workflows to the team members with respect to their departments. They have got a really cool feature of exporting their dashboards to PDF.
On the other hand, Elastic search comes with no UI of its own but the tasks can be inherited to Kibana and it has really very cool background themes that aren’t there in Splunk. So the dashboard personalization is kind of better in Kibana.
Conclusion: It totally depends on the choice of the user how the dashboards should be aligned as both of them provide some really very cool features but Splunk has got more features like exporting the dashboards as PDF’s and other client-facing graphs.
-
Splunk vs Elastic Search — The Data Migration and User Management
It actually depends on the type of data formats supported by both of these tools. Both Splunk and Elastic Search comes with data shipper object which actually retains the path of the files and uploads.
The mapping of the object with reference to its other counterparts’ fields is done very differently for both of them. As Splunk comes with inbuilt and pre-configured features which allows it to map the data into entities with respective values but on the other hand, we need to define the mapping of every filed type to its values in Elastic Search.
Another difference with data migration comes when the data is parsed as both of them have a way different approach for the same. Elastic search has taken parsing kind of for granted and very much manual but on the other hand, Splunk comes with pre-loaded wizards and features which are very easy and reliable for use.
Another very useful feature of user Management comes pre-installed with Splunk as it helps the managers to manage their resources who are working with the particular project logs and their segmentation. On the other hand, Elastic Search comes with no such features as they have pre-defined assignment logs.
Conclusion: Splunk is a very easy and reliable approach on part of data migrations and user management but Elastic Search is catching up really very fast with these features.
Splunk and Elastic Search Comparison Table
Below are the differences between Splunk and Elastic Search:
| Basis Of Comparision | SPLUNK | Elastic Search |
| Basics | The biggest problem with Splunk was and still is that it is an expensive and paid tool.
|
Elastic Search is a free and open-source solution.
|
| Target Problem and Solution | Splunk has traditionally served the big enterprise clients in past which are opting out for an on-premises solution because of the data integrity issues and now they are trying to capture the smaller companies as their client by making their services affordable. | Elastic Search, on the other hand, tends to provide end to end open source and some premium services for all kinds of companies out there in this domain. |
| Set-Ups
|
Splunk has distributed their services around two modules Splunk Enterprise targets the on-prem specializations and Splunk Cloud tries to serve the cloud-based specializations through the web app as both has comparatively similar features. The daily limits of usage are the things which are on the table for bargains with both the services. | On the other hand, Elastic Search has only one SaaS platform which has a paid module for deployment rest other modules are a free and open source which are really very helpful for small companies to monitor their enterprise logs without paying any money for their own data.
|
| The UI and Dashboards Visualizations | Eventually, Splunk has improved their user interface with new dashboard controls, good and interacting graphical interfaces and abilities to assign the tasks and workflows to the team members with respect to their departments. They have got a really cool feature of exporting their dashboards to PDF.
|
On the other hand, Elastic search comes with no UI of its own but the tasks can be inherited to Kibana and it has really very cool background themes which aren’t there in Splunk. So the dashboard personalization is kind of better in Kibana.
|
| Data Migration and User Management | As Splunk come with inbuilt and pre-configured features which allows it to map the data into entities with respective values.
Splunk comes with pre-loaded wizards and features which are very easy and reliable for use.
|
Elastic Search comes with no such pre-loaded wizards and features which are very easy and reliable for use. |
Summary: Splunk vs Elastic Search
In short, both Splunk and Elastic Search are competent, enterprise-grade log management and analysis platforms trusted by the world’s leading organizations.
Recommended Articles
This has been a guide to differences between Splunk vs Elastic Search. Here we discuss the head to head Comparison, key differences between the Splunk vs Elastic Search with infographics and comparison table. You may also look at the following articles to learn more –
- Splunk vs Tableau – Top 12 Comparison To learn
- Hadoop vs Splunk – Find Out The Best 7 Differences
- Cassandra vs Elasticsearch – Which One Is Better
- Hadoop vs Elasticsearch – Which one is More Useful
- Splunk vs Nagios Difference
- Amazing features of Hadoop vs Spark
- Top Differences of Graylog vs Splunk
- Key Differences of Datadog vs Splunk
