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Splunk Enterprise VS MyAnalytics

Compare Splunk Enterprise VS MyAnalytics and see what are their differences

Splunk Enterprise logo Splunk Enterprise

Splunk Enteprise is the fastest way to aggregate, analyze and get answers from your machine data with the help machine learning and real-time visibility.

MyAnalytics logo MyAnalytics

MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.
  • Splunk Enterprise Landing page
    Landing page //
    2023-03-28
  • MyAnalytics Landing page
    Landing page //
    2023-09-21

Splunk Enterprise videos

Webinar: Splunk Enterprise Security (Splunk ES)

MyAnalytics videos

No MyAnalytics videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Splunk Enterprise and MyAnalytics)
Monitoring Tools
100 100%
0% 0
Technical Computing
0 0%
100% 100
Log Management
100 100%
0% 0
Business & Commerce
0 0%
100% 100

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What are some alternatives?

When comparing Splunk Enterprise and MyAnalytics, you can also consider the following products

Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!

Arcadia Enterprise - Arcadia Enterprise is the ultimate native BI for data lakes with real-time streaming visualizations, all without adding hardware or moving data.

AppDynamics - Get real-time insight from your apps using Application Performance Management—how they’re being used, how they’re performing, where they need help.

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

GraphPad Prism - Overview. GraphPad Prism, available for both Windows and Mac computers, combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization.