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."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."
"The solution is user-friendly and has good performance and certification."
"The program is very stable."
"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."
"The most useful feature has been the AI/ML. The way BigPanda uses the AI/ML is good compared to other SRE tools."
"The most valuable features of BigPanda are the API integration was good. It enables us to do faster onboarding."
"A user-friendly solution."
"This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime."
"The solution is useful for monitoring logs."
"Flame graphs are pretty useful for understanding how GraphQL resolves our federated queries when it comes to identifying slow points in our requests. In our microservice environment with 170 services."
"Their interface is probably one of the easiest things to use because it lets non-developers and non-engineers quickly get access to metrics and pull business value out of them. We could put together dashboards and give it to people who are non-technical, then they can see the state of the world."
"This is definitely a good product and I would consider them one of the leaders within the application monitoring and cloud monitoring space."
"Profiling has been made easier."
"We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions."
"By moving to Datadog, we did not need to manage our own monitoring infrastructure anymore."
"The UI for this solution could be improved. It is very hard to find what you are looking for."
"BigPanda could improve by syncing its threshold settings with Dynatrace to align with users' familiarity."
"We had to use a partner for the deployment."
"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 usability needs to improve, because it is a pure code environment."
"Our infrastructure is quite large - tens of thousands of servers, often with 30-plus checks running on each host with one minute intervals. This generates a lot of data often in bursts (when we have a large scale failure). This has caused some delay in the ingestion pipeline."
"The observability can be enriched with regards to infrastructure and the application-integrated environment. The dashboard and reports could be improved."
"BigPanda attempts a little of everything and fails at most."
"Datadog could make their use cases more visible either through their docs or tutorial videos."
"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."
"Federated views for Datadog dashboards are critical as large companies utilize multiple instances of the product and cannot link the metrics or correlate the metrics together. This stunts the usage of Datadog."
"The on-premise version is very difficult to upgrade."
"Once agents are connected to the Datadog portal, we should be able to upgrade them quickly."
"I've found that the documentation is lacking in certain regards."
"Datadog could improve the flexibility with AI and ML concepts. This will allow customers to be more leveraged towards publishing."
"It does not have the best interface."
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