How often ChatGPT mentions Honeycomb for application performance monitoring tools — and how it stacks up against the tools that dominate the answers.
Share of ChatGPT answers naming each tool, same 10 questions.
| # | Tool | Visibility | |
|---|---|---|---|
| 1 | Datadog | 97% | |
| 2 | New Relic | 93% | |
| 3 | Dynatrace | 90% | |
| 4 | Grafana | 88% | |
| 5 | Splunk | 70% | |
| 6 | AppDynamics | 66% | |
| 7 | Sentry | 61% | |
| 8 | Tempo | 57% | |
| 9 | Prometheus | 57% | |
| 10 | Grafana Cloud | 56% | |
| 11 | Loki | 56% | |
| 12 | SigNoz | 55% | |
| 13 | Honeycomb ← this tool | 34% |
Free account — see every engine, the trend over time, and which sources to win.
The questions where ChatGPT currently names Honeycomb.
The APM market in 2026 is dominated by a few major platforms, but the “best” tool depends heavily on your stack, team size, budget, and observability maturity. The strongest platforms consistently mentioned across recent industry comparisons are Datadog, New Relic, Dynatrace, Grafana Labs, Elastic, Honeycomb, and SigNoz. Unanswered (+2 more citation)
ToolBest ForKey StrengthsMain TradeoffDatadogCloud-native & Kubernetes teamsHuge integration ecosystem, polished UX, unified observabilityExpensive at scaleDynatraceLarge enterprisesAI-driven root cause analysis, automation, OneAgentComplex + premium pricingNew RelicMid-market SaaS teamsStrong free tier, full-stack telemetry, NRQLUsage costs can spikeGrafana CloudOpenTelemetry & OSS-first teamsFlexible dashboards, Prometheus/Loki ecosystemMore operational overheadElastic ObservabilityLog-heavy organizationsExcellent search + ELK integrationSteeper tuning/maintenanceHoneycombDistributed tracing & debuggingPowerful high-cardinality tracingUX learning curveSplunk Observability CloudEnterprise observability + securityStrong analytics and tracingHigh costAppDynamicsTraditional enterprise Java/.NETBusiness transaction monitoringSlower innovation paceSentryDeveloper-first error monitoringExcellent exception tracking + performanceNot full infra observabilitySigNozOpen-source OpenTelemetry stacksSelf-hosted, lower cost, unified traces/logsSmaller ecosystem
Most teams evaluating premium APM today compare:
Datadog
Dynatrace
New Relic
These three dominate most enterprise evaluations and large-scale deployments. Nova AI Ops (+1 more citation)
The biggest trend in 2025–2026 is migration toward:
OpenTelemetry
Prometheus
Grafana
SigNoz
Elastic
Teams increasingly want vendor-neutral telemetry and lower ingest costs. CubeAPM (+2 more citation)
Strongest options:
Datadog
Dynatrace
Honeycomb
Grafana Cloud
Honeycomb especially gets praise for debugging complex distributed traces. Reddit (+1 more citation)
Community consensus in SRE/DevOps circles:
Datadog = best UX + integrations
Dynatrace = strongest automation/AI
New Relic = easiest entry point
Grafana = best OSS flexibility
Honeycomb = strongest tracing workflows
Biggest complaint across all premium vendors = pricing explosion at scale
Multiple Reddit threads mention Datadog and New Relic becoming very expensive once telemetry volume grows. Reddit (+2 more citation)
New Relic
Sentry
Grafana Cloud
Dynatrace
Datadog
Splunk Observability Cloud
Datadog
Honeycomb
Grafana Labs
Grafana Labs
SigNoz
Elastic
Sentry
Honeycomb
Datadog
Dynatrace
New Relic
Grafana Cloud
Honeycomb
These cover most modern observability needs across SaaS, enterprise, Kubernetes, and OpenTelemetry-first architectures. Unanswered (+2 more citation)