Datadog vs. Mode Analytics

As per my experience, Datadog is best suited for complex, cloud-native environments where unified observability is critical, as it integrates seamlessly with AWS and Azure. Moreover, it provides deep visibility into latency and error rates. Datadog pricing is less appropriate for Startups with a tight budget and for organizations needing advanced incident management.

Incentivized

Mode is a clear category winner for how it easy it is to go from interactive analysis to professional quality reporting. You can easily do all your SQL and quite a bit of R/Python. If you want to quickly go from your database to simple charts, this is your pick. If you need to do heavier data modeling, scheduling jobs, or ML, you'll need something else, like Databricks. In my opinion, the quality of visualizations and some developer/analyst features make Databricks an unacceptable substitute.

Incentivized

• The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
• Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
• Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.

Incentivized

• It allows me to undertake data visualization tasks by creating really insightful charts and dashboards
• It allows for easy sharing and work collaboration on data analysis tasks
• Mode has an easier to use SQL editor as well
• I love how it organizes all our SQL data tables into easy-to-view data we can draw insights on

Incentivized

• In my experience, .NET Tracing Agent caused severe and untraceable performance issues
• In my opinion, usage and billing structures were opaque and surprising
• In my experience, documentation was incomplete, contradicting or sometimes completely wrong, even for common infrastructure (AWS Fargate)
• I feel support was unhelpful at times, and bounced us back and forth to other teams
• In my opinion, multiple methods of sample rate control were ineffective, adding to excessive usage and cost

Incentivized

• Date ranges aren't always the most intuitive to set, strangely
• Faster refresh rates would be ideal
• Would love more dynamic mobile device integration (alerts, etc)

Incentivized

Definitely will not revisit after our issues and, in my opinion, poor support.

Incentivized

There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.

Incentivized

For the advanced user already familiar with Python. It is just the same tool, already managed and connected to the data.

Incentivized

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.

Incentivized

Mode has dedicated agents who are online in a chatroom, ready to take on any questions and provide helpful feedback.

Incentivized

Documentation was difficult to work through, rollout was catastrophic (completely outage)

Incentivized

Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.


Key features:


Logs, metrics, and APM (Application Performance Monitoring)


Real-time alerting and dashboards


Supports Kubernetes, AWS, GCP, and other integrations


RUM (Real User Monitoring) and Synthetics





✅ Best for backend, server, and distributed systems monitoring.

Incentivized

We used both Qlik and Mode at our organization. The mode was used a quick analysis SQL tool while Qlik was our enterprise BI solution.

Incentivized

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

Incentivized

• Extremely positive. It's a key feature in our application.
• Were it not for the account management bit, Mode would be hands-down our recommendation for anyone looking for cloud BI.

Incentivized