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
ScienceLogic SL1
Score 8.9 out of 10
Enterprise companies (1,001+ employees)
ScienceLogic is a system and application monitoring and performance management platform. ScienceLogic collects and aggregates data across and IT ecosystems and contextualizes it for actionable insights with the SL1 product offering.
N/A
Pricing
Datadog
ScienceLogic SL1
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
No answers on this topic
Offerings
Pricing Offerings
Datadog
ScienceLogic SL1
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
Required
Additional Details
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
ScienceLogic SL1 offers four tiers:
SL1 Advanced – Application Health, Automated Troubleshooting and Remediation Workflows
SL1 Base – Infrastructure Monitoring, Topology & Event Correlation
SL1 Premium – AI/ML-driven Analytics, Low-Code Automated Workflow Authoring
SL1 Standard – Infrastructure Monitoring – with Agents, Business Services, Incident Automation, CMDB Synchronization, Behavioral Correlation
To get pricing for each tier, please contact the vendor.
More Pricing Information
Community Pulse
Datadog
ScienceLogic SL1
Considered Both Products
Datadog
Verified User
Anonymous
Chose Datadog
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, …
Datadog is an all in one solution. It has everything in one place so you don't have to go from application to application and try to figure out what exactly happened. No more stitching database errors from one third party to backend errors in another to front end errors in …
Datadog crushed the competition on price and offering more solutions in one product cutting down on implementation time and effort while ensuring that the "integration" between one of their offerings was completely compatible with any of the others. I'm sure it's not the case …
We've completely replaced New Relic with Datadog and find it easier to use and more comprehensive. Our AWS and Sentry usage will continue for now. But Datadog gives us a much broader coverage - we can monitor our AWS services and many other services that interact with them. …
Dynatrace was cheaper but, in my opinion, its setup, features, and overall user experience do not come close to what Datadog can offer, making it more of a pain to use and not worth the cheaper cost over Datadog (especially if migrating away from Datadog to dynatrace).
The first reason for selecting Datadog was of course it's pricing which is quite better in terms of competitor like Appdynamics and splunk. Second thing is versatile services which they are offering on one platform which means entire end to end services can be monitor at one …
It's a one-stop solution for all our needs whereas in other open-source tools, we have an operational overhead to keep and manage the uptime of these tools as well and also manage their versioning, upgrade, and patching cycle. Also if there are any bugs then we have to raise an …
One of the most important reason is single agent configuration for all kinds of monitoring. It also proved an auto upgrade feature of agents that reduces the overhead. It also provides range of options when it comes to data visualization and dashboards. It also provide tagging …
Kubernetes with Prometheus and other open-source options. It is prone to more toil to set up but the stack can be largely replicated in open source technologies.
New Relic was a good tool but had really pushy salespeople. They also released a product called infrastructure recently, and it was worse than their previous product (servers). The previous product was also free! Needless to say, we will not be going back to New Relic any time …
Easier to set up and integrate with other auxiliary tools. The cost was also a benefit along with self-service capabilities. We could set up Data Dog by ourselves, versus needing to bring additional consulting efforts to setup Dynatrace. Reliability of results (less false …
Ultimately, Datadog had the most already-built bridges into our existing infrastructure -- third parties that we're using for certain services are far more likely to work with Datadog than other systems. This means that, while expensive, Datadog has done a tremendous amount of …
Datadog has been harder to setup out-of-the-box compared to its alternatives, although it's graphs and dashboards have been more useful. Other tools handle individual tasks better. For example, Splunk has been the best logging tool I've used, and New Relic is great for CPU and …
It has been easier to work with Datadog for all our business needs and get things on their roadmap if we found it lacking. Currently we use a mix of various tools as they were existing prior to Datadog came. We are evaluating new offering like Datadog's latest log management to …
I am listing how Datadog is better than below chosen NotSensu - Datadog has more integrations and easy to use UI. Prometheus - Datadog Integration are more in number than, simple installation process
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.
Geckoboard has nice dashboard options, however their third party system support isn't as strong as Datadog. Geckoboard did not support all the various server and development systems we use, whereas Datadog did. Also, Datadog has better alerting and monitoring options than …
Datadog empowers us to create dashboards and visualize the state of our infrastructure in real time. It gives us control over what we want to view and how. The graphs provide deep insight into trends and anamoly detectives. These features are lacking in some of the other …
ScienceLogic SL1 supports large scale of IT Infrastructure devices and vendors. Was the single tool providing multiple functionalities at same time and allowed to remove additional legacy tools used for monitoring. Allowed integration with incident management and CMDB. Allowed …
From a capability perspective they stack up very similar but from a look and feel, ScienceLogic SL1 one is miles behind the curve on all three. We chose SL because we already had elements of the service in place on our infrastructure from our previous MSP so they were a …
I see great potential and infact i do strongly beleive it offers even beter capabilities than the traditional tools out there but again it comes down to how well you have trained us on how to unlock these capabilities. I suggest incentives for techs for providing feedback for …
Geneos is more complicated and 'heavy' to setup. It requires a lot of expertise in setting up. Also the dashboards are not great. ScienceLogic SL1 works well for customer facing dashboards.
Entuity was lacking a lot of custom reporting and also the out of the box automation and RBA was also less. Our customers were mainly looking for devices which are next gen like sdwan which Entuity doesn't support. When it come to ScienceLogic SL1 it will support all sets of …
Galileo analyzes storage arrays and backups more thoroughly, but SL1 is much better for host and network monitoring. SL1 has some storage monitoring features for some storage arrays, but they are not as detailed.
I was not part of the team selecting ScienceLogic SL1. Our goal was to increase event visibility in our server environment. We were using scripting which created many false events. SolarWinds is primarily used in the Network space to monitor network gear.
Agentless product that can integrate easily with other product and also allow us to automate tasks, example closing tickets when events are cleared automatically which user interactions.
Just because Science logic provides much more better enhancement and getting improved everyday. The autonomous integration and overall customization provided by the SL1 Platform is outstanding. In every sections be it in Monitoring or checking system logs and provide the best …
Science logic SL1 is so user friendly and it's really easy to navigate between function. I would recommend Sciene logic SL1 to all of them who are looking for really useful monitoring tool and expecting easy way of managing it.
ScienceLogic SL1 has a greater understanding and maturity on what Infrastructure monitoring needs to be and has to include at a decent price point for what it offers compared to its competitors.
ScienceLogic SL1 comparing with ITM/Netcool monitoring has better price. It's more easy to implement and mange ScienceLogic SL1 then other monitoring tools.
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.
Appropriate if you are setting up a monitoring suite in new Infrastructure Environment. Definitely NOT suited for Migration Projects. ScienceLogic SL1 cannot cater to a lot of monitoring requirements which already would have been configured in old monitoring suite. Plus, limited support for customizations and having to go to "Feature Requests" route makes in extremely complicated.
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
Creating powerpacks from scratch for new devices may be straightforward but will rarely be easy. Rewarding when completed, but not easy.
Developer documentation needs a rethink. While the information may be there (it isn't always) it is not easy to find. This is not helped by using different terms for the same things.
A developer console/dashboard for monitoring data collection from powerpacks instances without having to switch webpages or have to monitor multiple webpages.
We migrated away from our 20-year-old homegrown solution and have no back-tracking capability. ScienceLogic is demonstrating new capabilities that we would not have been able to do on our own using our legacy system. We understand the capabilities of competitors based on our bake-off selection where ScienceLogic won on capabilities and future near-term potential (expandability, platform growth). We know that those competitors are not really close to where we have been able to push ScienceLogic (as a partner).
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.
We use ScienceLogic SL1 in our organization to serve effective monitoring solutions to our external customers. Our customers depend upon us for critical events/alerts related to their IT infrastructure gears and using SL1, we're able to provide them with a proactive monitoring solution that resolves an issue before an impact is noticed by the customer. There are very few monitoring solutions that can cater to a variety of Cloud platforms like Public Cloud (AWS, Azure) and private cloud simultaneously and SL1 addresses this business problem very well
Science Logic SL1 provides the option of Distributed deployment where multiple instances of each appliance can be deployed to manage the load and availability. SL1 provides a High Availability feature for Database Servers and Data Collection. If one of the Data Collectors in the collector group fails, it will automatically redistribute the devices from the failed Data Collector among the other Data Collectors in the Collector Group. The high availability feature for the Database server ensures that SL1 performs failover automatically to another server without causing the outage to the application.
The performance is entirely dependent on the complexity of the environment/network being used to host the platform. Outside of those factors, the platform runs very efficiently and quickly out of the box. We have integrations with other platforms and neither seem to take a hit from our moderate API usage. Any issues with performance would be experienced by choices made in infrastructure or complexity of things built by the customer to display in the GUI (overly complicated and cluttered dashboards for example)
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.
So far, it's good as part of my overall experience, except for a couple of use cases. The support team is well knowledgeable, has technical sound, and is efficient. When support escalates to engineering, the issue gets stuck and takes months to resolve.
When I joined our company, I did not know about the in person training at firts. Logging onto the SL University, I realised that there were different sessions being held at different times throughout the year. The training itself was good, but being in a different time zone, made it difficult to attend, but the sessions that I attended was great!
There are a lot of educational materials and courses on the SL1 training site (Litmos university). However the recording quality is sometimes not very good - screen resolution is low. There is a lack of professional rather than user-oriented documents and there are mistakes in documentation and education is not well structured.
Along with the purchase of the solution, we purchased a statement of work with their Professional Services organization to meet our outcomes and fill our critical gaps. The PS team was outstanding, very professional and allowed us to screen share while they built our integrations. In many cases they would teach us how they did certain things within the platform.
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.
We evaluated a couple of other competitive products in the IT infrastructure observability domain; however, we found that ScienceLogic has a slight edge over the others for us. We encountered a cost barrier, as managing too many customers with an MSP setup was a costly affair, and several solutions did not offer an MSP solution at that time.
Our deployment model is vastly different from product expectations. Our global / internal monitoring foot print is 8 production stacks in dual data centers with 50% collection capacity allocated to each data center with minimal numbers of collection groups. General Collection is our default collection group. Special Collection is for monitoring our ASA and other hardware that cannot be polled by a large number of IP addresses, so this collection group is usually 2 collectors). Because most of our stacks are in different physical data centers, we cannot use the provided HA solution. We have to use the DR solution (DRBD + CNAMEs). We routinely test power in our data centers (yearly). Because we have to use DR, we have a hand-touch to flip nodes and change the DNS CNAME half of the times when there is an outage (by design). When the outage is planned, we do this ahead of the outage so that we don't care that the Secondary has dropped away from the Primary. Hopefully, we'll be able to find a way to meet our constraints and improve our resiliency and reduce our hand-touch in future releases. For now, this works for us and our complexity. (I hear that the HA option is sweet. I just can't consume that.)