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
Logz.io
Score 8.3 out of 10
Small Businesses (1-50 employees)
Logz.io in Boston offers their enterprise-grade log analytics application, oriented towards providing data security and eliminating the need for capacity management.
$0.84
per ingested GB 3 day of log retention
Pricing
Datadog
Logz.io
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
Log Management - Community
$0
1 day of log retention.
Log Management - Pro
$.92
per ingested GB. 7 days retention.
Distributed Tracing - Pro
$5
Per million spans.
Infrastructure Monitoring - Pro
$12
per month per 1000 time-series metrics.
Log Management - Enterprise
Custom
Cloud SIEM - Enterprise
from $1.49
per ingested GB. Price includes Logz.io Log Management
Offerings
Pricing Offerings
Datadog
Logz.io
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
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).
Director Of Information Technology & Data Management
Chose Logz.io
Logz.io is more affordable, less work to maintain, and has more features. It was an easy choice. After my last team had to manage their own ELK stack, this was a no brainer. It helps us be focused on our core competencies.
It is more focused in its approach which makes it really good for aggregating and analyzing logs. It has been way more helpful than New Relic APM for us. Data dog is nice but has some different focuses as well.
If I want to see what customers are doing wrong in their sessions, we can do that easily. On the other hand, if we want to know the payload in the API calls, that is the area where Datadog can improve.
Logz.io is an effective solution if your alerting needs are fairly straightforward and you don't need long-term retention of logs with easy access. If being able to maintain easy access to logs longer than this is necessary, another solution might be better. If you need a high degree of precision with alerting triggers and the ability to suppress alerts, you will need to combine Logz.io with an integration to get this or you might consider a different solution.
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.
Its a one stop solution for most processes and does reduce cost overall. This does in turn help teams communicate in a much more efficient way, also RUM is a game changer for any quality product; we use RUM alot for debugging and reverse engineering issues. Reports and coverage has been a plus, it all has helped us a lot in our processes.
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.
I initially struggled trying to ensure the correct data was returned in the Kibana search, but I found it overall easy to use. Some of the UI is not as seamless as I'd expect, like changing the environment completely resets your search criteria and filters, which is annoying since it's a common use case to search something in multiple environments
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.
Their support team is the best in the world! They supported us in most of the critical times and helped to resolve the issue in real time. Also their email support is well maintained and never a mail is missed unanswered. Kudos to the support team of logz.io for maintaining professionalism.
In terms of usability, I’ve found Datadog significantly more approachable and powerful compared to Elasticsearch, especially for day-to-day operational monitoring. Datadog offers a much more cohesive, user-friendly interface out of the box, with built-in support for metrics, logs, tracing, alerting, and dashboards—all tightly integrated. In contrast, Elasticsearch often felt barebones and required considerable setup and additional tooling (like Kibana or Logstash) to reach the same level of functionality. While Elasticsearch is excellent for high-volume log ingestion and full-text search, it lacks the depth of features and real-time visualization capabilities that Datadog provides natively. The query language in Datadog is also quite usable and comparable for my needs—mainly filtering and aggregating logs and metrics—without needing to learn Elasticsearch's more complex DSL. Overall, Datadog saves our team time and effort, whereas Elasticsearch often felt like building a monitoring system from scratch. The all-in-one nature of Datadog, despite its complexity, is ultimately more efficient and scalable for our use case.
Logz.io is more affordable, less work to maintain, and has more features. It was an easy choice. After my last team had to manage their own ELK stack, this was a no brainer. It helps us be focused on our core competencies.