Overview
ProductRatingMost Used ByProduct SummaryStarting Price
AWS SaaS Boost
Score 8.7 out of 10
N/A
AWS SaaS Boost is an open source reference environment that helps Independent Software Vendor (ISVs) accelerate their move to Software-as-a-Service (SaaS). From small specialized software businesses to large global solution providers, AWS SaaS Boost aims to helps users accelerate moving applications to AWS with minimal modifications. Users can build, provision, and manage a SaaS environment with greater confidence based on AWS best practices and proven patterns from hundreds of successful…N/A
Datadog
Score 8.8 out of 10
N/A
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.
$18
per month per host
Pricing
AWS SaaS BoostDatadog
Editions & Modules
No answers on this topic
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
Offerings
Pricing Offerings
AWS SaaS BoostDatadog
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional DetailsDiscount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
More Pricing Information
Community Pulse
AWS SaaS BoostDatadog
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User Ratings
AWS SaaS BoostDatadog
Likelihood to Recommend
8.0
(1 ratings)
9.6
(46 ratings)
Usability
-
(0 ratings)
9.3
(25 ratings)
Support Rating
-
(0 ratings)
8.9
(6 ratings)
User Testimonials
AWS SaaS BoostDatadog
Likelihood to Recommend
Amazon AWS
AWS SaaS Boost provides us with effective visualization capabilities of data. It also enables us integrate with a number of software but with some limitations. It has wonderful data merging capabilities .Boost's code is customizable enabling us modify it to meet our environmental requirements when needed. To use it well, one has to have high coding skills and should be familiar with AWS entanglements.
Read full review
Datadog
Datadog works really well with complex microservices architecture like any E-commerce platform which will be having multiple services but they all are interdependent to others so in this scenario Datadog will be best to monitor these as it will show the transactions also between those microservices. If you are using multiple services in your architecture whether it will be cloud services or on prem services Datadog will be the best choice to monitor all those service with in Datadog so that you can see everything in a single place. But if you are having small architecture and few services in that then in that scenario you can use Datadog but it will be little costly as compared to other but obviously the features are very well.
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Pros
Amazon AWS
  • Easy delivery of solutions to SaaS models.
  • consolidation of data
  • Open source
Read full review
Datadog
  • Create Dashboards as per application, environments, and Custom metrics in one panel.
  • Log aggregation, one-stop Application monitoring tools for the whole infrastructure.
  • Playbooks, SLA definition, success and error quotas, request visualizations.
  • DB monitoring, Serverless stack monitoring.
  • Alerting of Production incidents so we can quickly resolve the issues on time.
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Cons
Amazon AWS
  • limited integration
  • One has to be at home with AWS complexities to effectively use it
Read full review
Datadog
  • 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
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Usability
Amazon AWS
No answers on this topic
Datadog
There is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.
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Support Rating
Amazon AWS
No answers on this topic
Datadog
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.
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Alternatives Considered
Amazon AWS
No answers on this topic
Datadog
We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.
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Return on Investment
Amazon AWS
  • Supports app transformations to SaaS, minimizing development work
  • Reduces time for development and experimenting, enabling faster delivery of software to our clients.
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Datadog
  • 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.
Read full review
ScreenShots

Datadog Screenshots

Screenshot of the out-of-the-box and customizable monitoring dashboards.Screenshot of Datadog's collaboration features, where users can discuss issues in-context with production data, annotate changes and notify their teams, see who responded to that alert before, and discover what was done to fix it.Screenshot of where Datadog unifies traces, metrics, and logs—the three pillars of observability.Screenshot of some of Datadog's 400+ built-in integrations.Screenshot of Datadog's Service Map, which decomposes an application into all its component services and draws the observed dependencies between these services in real timeScreenshot of centralized log data, pulled from any source.