Datadog vs Sysdig: What are the differences?
Developers describe Datadog as "Unify logs, metrics, and traces from across your distributed infrastructure". Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!. On the other hand, Sysdig is detailed as "Open source container monitoring for all Linux container technologies, including Docker, LXC, etc". Sysdig is open source, system-level exploration: capture system state and activity from a running Linux instance, then save, filter and analyze Sysdig is scriptable in Lua and includes a command line interface and a powerful interactive UI, csysdig, that runs in your terminal. Think of sysdig as strace + tcpdump + htop + iftop + lsof + awesome sauce. With state of the art container visibility on top..
Datadog belongs to "Performance Monitoring" category of the tech stack, while Sysdig can be primarily classified under "Monitoring Tools".
Some of the features offered by Datadog are:
- 14-day Free Trial for an unlimited number of hosts
- 200+ turn-key integrations for data aggregation
- Clean graphs of StatsD and other integrations
On the other hand, Sysdig provides the following key features:
- Real-Time Dashboard
- Historical Replay
- Dynamic Topology
"Monitoring for many apps (databases, web servers, etc)" is the top reason why over 118 developers like Datadog, while over 2 developers mention "Easy setup" as the leading cause for choosing Sysdig.
Sysdig is an open source tool with 5.68K GitHub stars and 526 GitHub forks. Here's a link to Sysdig's open source repository on GitHub.
Shopify, Salesforce, and Starbucks are some of the popular companies that use Datadog, whereas Sysdig is used by Vungle, CommonBond, and Gini. Datadog has a broader approval, being mentioned in 532 company stacks & 213 developers stacks; compared to Sysdig, which is listed in 5 company stacks and 4 developer stacks.
I haven't heard much about Datadog until about a year ago. Ironically, the NewRelic sales person who I had a series of trainings with was trash talking about Datadog a lot. That drew my attention to Datadog and I gave it a try at another client project where we needed log handling, dashboards and alerting.
In 2019, Datadog was already offering log management and from that perspective, it was ahead of NewRelic. Other than that, from my perspective, the two tools are offering a very-very similar set of tools. Therefore I wouldn't say there's a significant difference between the two, the decision is likely a matter of taste. The pricing is also very similar.
The reasons why we chose Datadog over NewRelic were:
- The presence of log handling feature (since then, logging is GA at NewRelic as well since falls 2019).
- The setup was easier even though I already had experience with NewRelic, including participation in NewRelic trainings.
- The UI of Datadog is more compact and my experience is smoother.
- The NewRelic UI is very fragmented and New Relic One is just increasing this experience for me.
- The log feature of Datadog is very well designed, I find very useful the tagging logs with services. The log filtering is also very awesome.
Bottom line is that both tools are great and it makes sense to discover both and making the decision based on your use case. In our case, Datadog was the clear winner due to its UI, ease of setup and the awesome logging and alerting features.
I chose Datadog APM because the much better APM insights it provides (flamegraph, percentiles by default).
The drawbacks of this decision are we had to move our production monitoring to TimescaleDB + Telegraf instead of NR Insight
NewRelic is definitely easier when starting out. Agent is only a lib and doesn't require a daemon
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