We performed a comparison between BigPanda and Datadog based on real PeerSpot user reviews.
Find out in this report how the two AIOps solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."One of the most valuable features of BigPanda is its user-friendly interface."
"Easy integration - We've had challenges in the past integrating all of our various monitoring sources and tools into one central system. BigPanda, with the integrations that it already has, as well as offering webhook/REST API, has made it very easy for us to plug everything in."
"The main thing that we like about BigPanda is the user interface."
"The event correlation is really good and it is able to reduce the noise. It is a good tool for anomaly detection."
"We have also made extensive use of the outbound integrations to ticketing systems (JIRA) and collaboration tools (Slack). The main driver for us has been getting all alerting into a single UI and enabling us to streamline our incident management process."
"A user-friendly solution."
"BigPanda integrates well with other solutions, such as WatchGuard,"
"Alert aggregation was the primary requirement. BigPanda pulls all this together into a single UI for us, allowing us to see related alerts grouped together into an incident, and enables us to easily create a JIRA ticket and Slack channel to manage an issue."
"We find they have a very helpful alert system."
"Datadog helps us detect issues early on and helps in troubleshooting."
"Having a wealth of information has helped us investigate outages, and having historical data helps us tune our system."
"Datadog's seamless integration with Slack and PagerDuty helped us to receive alerts right to the most common notification methods we use (our mobile devices and Slack)."
"Datadog's ability to group and visualize the servers and the data makes it relatively easy for the root cause analysis."
"This is definitely a good product and I would consider them one of the leaders within the application monitoring and cloud monitoring space."
"APM and tracing are super useful."
"The solution has helped our organization with custom events to track specific cases."
"The cost of this product is too high compared to New Relic."
"We had to use a partner for the deployment."
"BigPanda attempts a little of everything and fails at most."
"The solution could improve by having better integration."
"The UI for this solution could be improved. It is very hard to find what you are looking for."
"Analytics is an area for improvement, being able to break down the actions that are being taken by users of BigPanda, as well as the auto-magical work that is being done by BigPanda."
"BigPanda can improve the correlations. We didn't see any big value. It is still good at the same event deduplication, event processing, and ticket creation, but I was more looking at event analysis and event correlation. In that area, it is still no big difference between the other solutions on the market. All of them, are in the same immature stage."
"The observability can be enriched with regards to infrastructure and the application-integrated environment. The dashboard and reports could be improved."
"It can have a more modernized pricing mechanism. We're actually working with them to figure out how to become more modular and have a better and more modernized pricing mechanism. The issue with Datadog is that you have to buy the whole suite of different products, and you kind of get stuck in the old utilization of 40% of their suite. Most organizations today break down between application development, networking, and security. Therefore, there should be a way to break down different modules into just app dev, infosec, networking, etc. Customers have various needs across their business lines, and sometimes, they're just not willing to have tools that they're not using 100%. AppDynamics is probably a little bit better in terms of being modular."
"The product needs to have more enterprise approach to configuration."
"It could use some additional features when working with metrics like Grafana or like New Relic has. Datadog does not use library technologies like Dynatrace does. Datadog has machine learning too, but it does not have this option in all layers of monitoring like infrastructure service process in applications."
"The incident management beta looks promising, but it is still missing the ability to automatically create incidents based on certain alerts."
"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."
"The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances."
"Datadog has a lot of documentation, but a lot of that documentation assumes you know how the service works, which can lead to confusion."
"The product needs a better Datadog agent installation."
BigPanda is ranked 13th in AIOps with 12 reviews while Datadog is ranked 1st in AIOps with 137 reviews. BigPanda is rated 7.2, while Datadog is rated 8.6. The top reviewer of BigPanda writes "Offers comprehensive alert monitoring and a user-friendly interface but requires manual validation to provide accurate alerts". On the other hand, the top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". BigPanda is most compared with ServiceNow, Moogsoft, PagerDuty Operations Cloud, IBM Tivoli NetCool OMNIbus and Splunk ITSI (IT Service Intelligence), whereas Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and AppDynamics. See our BigPanda vs. Datadog report.
See our list of best AIOps vendors and best IT Infrastructure Monitoring vendors.
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There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitoring. We maintain critical processing on our mainframe so there was a desire to include this in our transaction trace. Due to a highly mature ELK implementation, we are not trying to incorporate log analytics into solution buy may consider in the future. We had AppD, Dynatrace, New Relic, and CA Wily all in house at the time of our evaluation. We eliminated Datadog due to a lack of real user monitoring and AppD based on experience and licensing. Between Dynatrace and New Relic, Dynatrace won based on the automation, integrated AI, support for "old" techs, and confidence we could eliminate multiple APM and infra monitoring tools.
I would not include products like BigPanda, MoogSoft, in this analysis. They are not monitoring solutions but event correlation solutions. You will need additional monitoring products to capture data and feed them. Having said that if you cannot consolidate tools you will likely need to purchase an event solution to make sense of all the alarms. We did evaluate these products but with Dynatrace AI did not feel the business value was there for the investment.
Here's a quick pro/con list on Dynatrace & New Relic from our analysis.
New Relic Pros: Insights is an awesome product and capability. Lots of capabilities and plugins to extend data collection. The APM dashboard is aesthetically pleasing and intuitive. Good training and documentation are available to support the product.
New Relic Cons: Requires lots of manual configurations to implement and support. Insights product requires an investment of time to achieve value. Licensing is a nightmare as there is virtually no transparency in what you are being charged for. Lack of solution to consolidate alerts across implementation other than significant investment in insights to manually achieve this.
Dynatrace Pros: Very simple to implement and maintain with out of the box automation which supports modern (cloud/Kubernetes) and "old" (mainframe). In-app chat is helpful. High integration of infra and APM data for full-stack observability and engineering. Topology and trace discovery is more reliable than other products or our CMDB. Synthetics are easy to set up for any user. AI-assisted problem analysis on the trace discovery streamlines troubleshooting. AI includes "events" in an analysis like VMotion, deployment events. Have not done yet but looking to leverage monitoring as code for a fully integrated and automated delivery pipeline. See keptn.sh open source project.
Dynatrace Cons: User SQL lacks some functions of NRQL for user analysis. Host, process, and service data is not available to query within the product. Alarm processing lacks some granular controls. The Plug-in library is less robust.
Good luck with your decision!
We are currently going through a paper-based analysis to select an Enterprise APM solution.
Our Contenders are
1. Dynatrace
2. Cisco(AppDynamics)
3. Broadcom DX-APM
Shortlisted based on existing relationships with other products and services they provide.
We discounted New Relic- despite their growing capability - as they are yet to enter the enterprise APM solution scene.
With regards to your response "We eliminated Datadog due to a lack of real user monitoring and AppD based on experience and licensing .." :
Will you be willing to expand on Appd - what was your experience and issues w.r.t licensing. These could help us with our evaluation. Much appreciated. Regards Adrian
Could you please share your requirements ? There are a lot tools can be added to the list. I spent almost 6 months to test and check many tools then I select eG enterprise.
Thanks