Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
$1.27
per month (billed annually) per host
Omnissa Intelligence
Score 9.8 out of 10
N/A
Omnissa Intelligence (formerly Workspace ONE Intelligence for Consumer Apps, or Apteligent Crittercism) is a Mobile APM and crash reporting tool. Its optimization for mobile environments allows it to handle the variety of configurations that come with mobile spaces, and can differentiate issues between applications and specific device environments (Android phone vs. iPhone vs. iPad, etc.). It automates issue detection and reporting, including how network issues impact application functionality…
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Pricing
Datadog
Omnissa Intelligence
Editions & Modules
Log Management
$1.27
per month (billed annually) per host
Infrastructure
$15.00
per month (billed annually) per host
Standard
$18
per month per host
Enterprise
$27
per month per host
DevSecOps Pro
$27
per month per host
APM
$31.00
per month (billed annually) per host
DevSecOps Enterprise
$41
per month per host
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Offerings
Pricing Offerings
Datadog
Omnissa Intelligence
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
A one-stop solution for everything you need. Multiple functionalities are tailored to meet specific business needs. Logs are essential for any business, and Datadog manages logs effectively. Rum sessions are something new to me and have given us a new perspective on how to reverse engineer issues that we see for our customers.
Crittercism is definitely, in my opinion, best for software testers/engineers. We are the faces behind proper app behavior. However, I'm sure there are other scenarios that would benefit from this program. Engineers should should use it prior to sending out builds to see if anything major is crashing or going wrong behind the scenes to diagnose the problem before going into testing/production
Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
I would appreciate more supportive examples for how to filter and view metrics in the explorer
I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
Datadog's user interface is quite friendly and easy to navigate. With menus clearly categorized, and ability to bookmark important dashboards, one can easily find what they're looking for. For dashboards, ability to move and resize visualizations and group them, is really helpful to organize dashboards. Automatic suggestions from Datadog for important visualizations based on the metrics and logs would provide another level of ease of use.
The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
I selected Datadog because of its features and the wide range of integration support. As I already told it supports more that 600+ integrations which helps and organization to keep everything in a single place and also its AI feature which is reducing the time for root cause analysis. Its custom dashboards features which helps us to visualize the data in a more attractive way.
I use both for different purposes. Twitter Fabric integration was easier for setup purposes and documentation was a lot clearer than Crittercism and geared towards Swift more so than Objective-C. Twitter Fabric is also better with real-time emails pointing to exact line number for a bug. Crittercism is better for bread crumb trails and stack traces to see the user flow and how a problem ending up becoming a problem in the first place.
