Archynt vs Datadog

Datadog processes telemetry at a scale we're nowhere near and have no plans to get near. If what you need is a place to store terabytes of logs, alert on p99 latency across a thousand hosts, and page someone at 3am, Datadog already does that better than a comparison page could argue otherwise. We say this upfront because most "X vs Y" pages pretend to be neutral and then spend six paragraphs undermining the competitor. We'd rather tell you where we actually differ and let you decide if it matters to you.

What Datadog doesn't do

Datadog's Software Catalog can link a service to its repository, and Universal Service Monitoring maps dependencies from eBPF without touching application code — both genuinely good pieces of engineering. What it doesn't do is parse the source itself: it knows a service has a repo, not what the code inside that repo actually depends on, imports, or calls. It sees the wire, not the code that produced the traffic on it.

That gap is the whole reason Archynt exists. We parse the repository — Java/Spring, Node, Python, Go — into a structural graph of services, endpoints, data stores and the relationships between them, then correlate that against what the runtime agent actually observes. Every dependency edge is tagged static, runtime, or both, and the mismatches between those two views are exactly where architectural drift and hidden risk live. That's a fundamentally different question than "what's my error rate right now," and it's not one Datadog's product is built to answer, because it's not trying to.

Where we'd point you at Datadog instead

If your actual problem this quarter is incident response, alerting fatigue, or you need one pane of glass for infrastructure metrics across hundreds of services — that's Datadog's core business, and we'd tell you to go use it. Archynt can ingest metrics from a Prometheus setup you already have and fold them into the architecture graph, but we have no interest in becoming a second place to store your telemetry. That's commodity, it's expensive to do well at scale, and Datadog already won that fight.

Where we'd point you at Archynt instead

If the question keeping you up is "does anyone actually know what depends on what in this system anymore," or "did that AI-generated PR just introduce a circular dependency nobody caught in review" — that's ours. The PR check and the MCP server both exist because that question needs to get answered before a merge, not after an incident.