Pricing, Features, and Deployment Compared
Datadog is a capable, mature observability platform, but its pricing is built from many separate meters – infrastructure hosts, APM hosts, log ingest and indexing, indexed spans, custom metrics, RUM, synthetics, and support – each with its own billing unit. Costs compound as usage grows and become hard to forecast; at scale, log indexing alone can dominate the bill, and SaaS delivery adds cloud egress fees that never appear on the Datadog invoice.
This guide compares five Datadog alternatives – CubeAPM, New Relic, Dynatrace, Grafana Cloud, and Elastic APM – on pricing, features, and deployment, so you can match the right platform to your cost ceiling, data-residency needs, and OpenTelemetry strategy.
All estimates assume a mid-scale reference scenario: 30TB/month (~20TB logs, 7TB traces, 3TB metrics), 100 hosts, 20 users, 30-day retention, core observability only. Estimates are directional, based on public rate cards as of early 2026; discounts can reduce SaaS costs significantly.
Why Teams Look Beyond Datadog
- SKU sprawl: costs build across hosts, logs, spans, custom metrics, RUM, synthetics, and support, each metered separately with its own limits.
- Log indexing dominates: at 30TB/month with 30% of logs indexed, indexing alone can reach ~$30,000/month.
- Coupled APM and infrastructure: APM hosts must also carry Infrastructure Monitoring, so adopting APM grows the baseline bill.
- Residency gaps and egress: CloudPrem is limited to logs and remains in preview with feature gaps, with no self-hosted setup for traces; external SaaS also incurs ~$0.10/GB egress (~$3,000/month at 30TB).
1. CubeAPM
Best for: DevOps and platform teams that want full-stack observability inside their own cloud without SaaS data egress, pricing sprawl, or DIY self-hosting overhead
CubeAPM is a self-hosted, OpenTelemetry-native, full-stack observability platform that runs inside your own AWS, GCP, or Azure VPC, so telemetry data stays inside your infrastructure. CubeAPM monitors the setup remotely. Pricing is a single meter – data ingested – so hosts, users, and custom metrics never add line items.
Used by Delhivery, Mamaearth, and world’s largest bus aggregator – redBus (part of MakeMyTrip Limited (NASDAQ: MMYT), 8+ countries), among others. SOC 2 Type II and ISO 27001 certified, rated Capterra 5/5 and G2 5/5.
Key Features
- OpenTelemetry-native: compatible with OpenTelemetry, Datadog, New Relic, Elastic, and Prometheus agents for incremental migration
- Self-hosted, vendor-managed: runs in your VPC with zero cloud egress cost (~$3,000/month saved at 30TB), and your monitoring stays up even if the internet doesn’t
- Full MELT coverage, AI-based Smart Sampling, unlimited retention, and an MCP server to query CubeAPM in natural language
- 800+ integrations: APM, logs, infrastructure, Kubernetes, synthetic monitoring, RUM, and error tracking
Pricing
Ingestion-based, predictable pricing of $0.15/GB. No per-user, per-host, or custom metric fees, with unlimited users and retention included. At 30TB/month: ~$5,100/month all-in.
Delhivery: 75% cost reduction after replacing three separate monitoring tools. Mamaearth: ~70% savings, migrated in under an hour.
- Pro: predictable single-dimension pricing; data never leaves your VPC; no egress; direct engineering support via WhatsApp and Slack, which responds in minutes
- Con: requires self-hosted deployment in cloud or on-prem; may not suit teams looking for a SaaS-only model.
- Con: AI/ML anomaly detection is growing but not as mature as Dynatrace Davis AI
2. New Relic
Best for: Teams that want a mature SaaS platform with broad full-stack coverage, native OTLP ingest, and strong application monitoring workflows
New Relic is a full-stack SaaS platform covering APM, infrastructure, browser, mobile, synthetics, and logs, with native OTLP ingest as its recommended data path and 780+ quickstarts. Its usage-based model splits cost between data ingested and per-user seats, so it grows with both volume and team size. A free tier offers 100GB per month plus one full-platform user.
Pricing: Data at $0.40/GB (Data Plus $0.60/GB), full platform users at $99 to $349 per user per month for full platform access. At 30TB/month: ~$20,000-$25,000+/month.
- Strengths: broad full-stack coverage, native OTLP ingest, and a generous free tier. Watch-outs: SaaS-only with regional data centers that may not meet strict residency rules, and NRQL lock-in that adds migration work.
3. Dynatrace
Best for: Large enterprises that need AI-automated root cause analysis and deep full-stack monitoring
Dynatrace pairs its Davis AI engine – automatic baselining, anomaly detection, and causal root-cause analysis – with OneAgent automatic discovery, and Gartner ranks it highest in Ability to Execute. It supports OpenTelemetry via OTLP but trades Datadog’s SKU sprawl for memory-GiB-hour billing that is harder to estimate.
Pricing: usage-based. Full-Stack at $0.01/memory-GiB-hour, log ingest at $0.20/GiB, retention billed separately. At 30TB/month: ~$20,000-$35,000+/month.
- Strengths: best automated root cause analysis and deep full-stack monitoring. Watch-outs: proprietary OneAgent lock-in, memory-GiB-hour pricing that is hard to estimate, and SaaS-only for most deployments.
4. Grafana Cloud (LGTM Stack)
Best for: OTel-first teams that want flexible dashboards and open-source foundations
Grafana Cloud is the managed LGTM stack – Loki, Grafana, Tempo, and Mimir – with the strongest dashboarding in the category, Grafana Alloy for OTLP ingestion, and integrated k6 load testing. It is fully OTel-native, so there is no custom-metrics penalty, and a self-hosted OSS path exists for teams with operational capacity.
Pricing: usage-based. Logs/traces at $0.50/GB ingested, metrics at $6.50/1k active series. At 30TB/month (managed): ~$15,000-$20,000+/month; Adaptive Metrics and Logs can reduce this.
- Strengths: fully OTel-native, the strongest dashboarding in the category, and a self-hosted option. Watch-out: no native APM out of the box, and a steep LGTM learning curve.
- At scale, self-hosted Grafana is prone to performance degradation; query times increase and dashboard load slows as data volume and user count grow
5. Elastic APM
Best for: Teams already on the Elastic Stack that want flexible deployment with strong search, logs, and APM
Elastic APM extends Elasticsearch with distributed tracing, service maps, and ML-based anomaly detection, correlating traces with logs in the same query interface. Teams can deploy it as SaaS or self-managed. Note: the OSS version reached end-of-service in September 2025.
Pricing: self-hosted is free (you cover infrastructure); Elastic Cloud Hosted from $99 to $184/month. At 30TB/month (Elastic Cloud): ~$8,000-$15,000/month.
- Strengths: strong log and trace correlation and a self-hosted option that keeps data in your environment. Watch-outs: significant operational overhead at scale, KQL’s learning curve, and the 2021 SSPL licensing change to review.
Cost Comparison at 30TB/Month Ingestion
| Tool | Est. Cost @ 30TB/mo | Pricing Model | OTel Native | Data Residency | Self-Hosted |
|---|---|---|---|---|---|
| CubeAPM | ~$5,100/mo all-in | $0.15/GB ingestion-based | Native | Always (in-VPC) | Yes (vendor-managed) |
| Elastic APM | ~$8K-$15K | Deployment-based | Supported | If self-hosted | Yes |
| Grafana Cloud | ~$15K-$20K+ | Usage-based | Native | If self-hosted | Yes |
| New Relic | ~$20K-$25K+ | Data + users | Supported | SaaS only | No |
| Dynatrace | ~$20K-$35K+ | GiB-hour + commit | Supported | Managed option | Managed |
| Datadog (ref.) | ~$30K-$45K+ | Host + feature-based | Supported* | SaaS only | Logs-only (preview) |
* OTel metrics in Datadog are often billed as custom metrics; its CloudPrem self-hosting is limited to logs and remains in preview. New Relic shows full platform users at $99 to $349 per user per month for full platform access. Vendor discounts and EDP commitments can significantly reduce SaaS costs.
To model your current Datadog bill before committing to a switch, the Datadog pricing calculator breaks down every cost dimension: hosts, log indexing, custom metrics, APM spans, and cloud egress.
How to Migrate Away from Datadog
- Audit and prioritize: list what your team actively uses across infrastructure, APM, logs, dashboards, monitors, and integrations, and separate must-haves from nice-to-haves.
- Reroute and validate: OTel-based telemetry is easiest to reroute; larger teams prefer OTel-led dual-write before cutover. Rebuild dashboards and alerts, then validate log search and trace correlation before turning Datadog off.
Which Datadog Alternative Is Right for You?
- CubeAPM: cost predictability and data sovereignty. Predictable $0.15/GB pricing collapses Datadog’s many meters into one, and it runs in-VPC with zero egress.
- New Relic: a mature SaaS platform with broad full-stack coverage, native OTLP ingest, and a free tier to start.
- Dynatrace: enterprise AI automation and causal root-cause analysis across complex estates.
- Grafana Cloud: OTel-first teams that want maximum dashboard flexibility and open-source foundations.
- Elastic APM: teams already on the Elastic Stack that want search, logs, and APM together.
When Datadog Is Still the Right Choice
Datadog is best for teams that want one mature SaaS platform for observability, security, APM, logs, RUM, synthetics, and integrations, and where cost is not a constraint.
- Your usage fits within budget and the bill stays predictable
- You want one vendor across infrastructure, APM, logs, RUM, synthetics, and security without stitching tools together
- Your team actively uses several Datadog modules, and migration work may outweigh the savings
- The integration ecosystem matters – Datadog’s 1,000+ integrations are hard to replicate quickly
Final Thoughts
Most teams leave Datadog over cost, not capability: SKU sprawl, log-indexing charges, and coupled APM billing all compound as usage grows. Among the alternatives, CubeAPM and Elastic make the strongest case for cost predictability and data ownership, Dynatrace offers the deepest AI-driven automation, Grafana Cloud the most flexible dashboarding, and New Relic the broadest full-stack SaaS coverage.
Before switching, model your real telemetry volume, retention needs, residency requirements, and OpenTelemetry usage against your top two options – those numbers decide it more clearly than any feature checklist.
