Updated March 15, 2023
Difference Between Datadog vs Splunk
The Datadog is a type of monitoring tool mainly used for the cloud-based application to monitor the database, services, servers, and other devices and also measure the performance of the applications. The Datadog tool uses the Software as the service (SaaS) platform for implementation in the application. Splunk is a tool used for log management of devices and analyses the data generated from devices. The Splunk tool analyzes the data generated from the machine and then converts the unstructured raw data into some human-readable form.
Head to Head Comparison between Datadog vs Splunk (Infographics)
Below are the top 6 differences between Datadog vs Splunk:
Key Differences between Datadog vs Splunk
Following are the key differences of Datadog vs Splunk:
Datadog Tool
- The Datadog tool can be categorized as the analytic or monitoring tool, which the DevOps and IT departments can use for monitoring the performance of cloud services and other infrastructure.
- The Datadog tool is used to monitor the performance of servers, tools, and databases.
- The Datadog tool supports different operating systems, i.e., Linux, Windows, and Mac operating systems. And the device can be deployed as SaaS (Software as a service).
- The backend technology used by the Datadog tool is Kafka, Apache Cassandra, and PostgreSQL.
- The Datadog tool supports the network’s multiple cloud visibility, which helps monitor the data and performance of cloud services.
- The dashboards used by the tool can be customized per the requirements, and the IT and DevOps teams can use the tool to monitor the performance of cloud services.
- The tool can be used for integrating several other products so that performance can be measured better for cloud services.
- When any issue occurs in the service, the tool can be used to generate alerts so that they can be taken care of immediately.
- The programming language supported by the Datadog tool is PHP, Go, .NET, Ruby, JAVA, Node, and python.
- The implementation and installation of the Datadog tool are easy and come up with different features. There are fewer features implemented in the tool.
Splunk Tool
- The use of the Splunk tool is there when there is a requirement to manage the data generated from the devices.
- The machines installed in the network generated continuous data, which requires some tools to analyze the data and develop some results from the data generated.
- The tool is used for monitoring and analyzing the data generated from various types of machines. The Splunk tool converts the data into a human-readable form so the developers can analyze it properly.
- The Splunk tool converts the raw data generated from the machine to human-readable form to analyze the data and logs of the device.
- There are three stages in the Splunk tool for processing data. In the first stage, data and the proper solution for the data analysis are identified. In the second stage, data conversion is there. In the final stage, the report is made from the data conversion.
- The data generated from a machine can be in any form, both structured and unstructured form. The tool can convert unstructured data to some human-readable structure so that it can be used to decide that.
- The log files generated from the machines can also be analyzed using the Splunk tool. The tool uses the search processing language to find any terms in a log file.
- The tool supports multiple data formats as an input file for data analyses. The data formats supported by the Splunk tool are .json, .xml, and .csv format.
Datadog vs Splunk Comparison Table
Let us discuss the top comparison between Datadog vs Splunk:
|
Datadog |
Splunk |
| The Datadog tool does not support multiple types of data formats. | The Splunk tool provides support to multiple types of data formats like.xml, .csv and .json files. |
| The Datadog tool is a type of monitoring tool which is used for monitoring the performance of cloud services. The tool can analyze the performance of servers, databases. | The Splunk tool is a type of log management tool which is used for analyzing the data which generates from the machine. The log files can be analyzed by the Splunk tool. |
| The dashboard used in the Datadog tool can be easily customizable as per the requirements. | There is no such option in the Splunk tool. The dashboard can not be customized or changed. |
| The configuration and installation of the Datadog tool are comparatively easy from the Splunk tool. As the tool uses the SaaS service the installation of software is easy. | The configuration and installation of Splunk tools are not easy when it is compared to the Datadog tool. |
| The Datadog tool generates an alert when there is something wrong in the tool and helps to identify the issue in the system. | There is no such option of generating alerts by the tool for the system. |
| There is no such option present in the Datadog tool for analyzing the data in real-time. | The data can be visualized in real-time by the Splunk tool which helps to properly analyze the data. |
| The implementation of the tool is cheap when it is compared to other tools like the Splunk tool. The features of the tool are cheap and easy to install in the system. | The implementation of the tool is expensive when it is compared to other tools like the Datadog tool. The Splunk tool features are a bit expensive for installation in the system. |
| The Datadog tool does not support the front-end application it only supports the back-end applications. | The Splunk tool supports the front-end application. The GUI is supported by the tool for the system. |
| The Datadog tool always has a stability issue as the tool is not stable with all the features. | There is no such problem in the Splunk tool as the tool is stable compared to other tools like Datadog. |
Conclusion
The Datadog tool is a performance measurement tool for the cloud service that helps to measure the performance of databases and servers. The Splunk tool is a type of log management tool which allows to analyze the log files generated from the machine and convert raw data to some human-readable form.
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