Pricing, Features, and Deployment Compared
New Relic delivers full-stack observability across metrics, events, logs, and traces. But for many engineering teams in 2026, three structural issues are forcing a serious evaluation of alternatives: per-seat pricing that compounds as teams grow ($49 to $349/month for full platform access per user), NRQL lock-in that makes every dashboard and alert non-portable, and a SaaS-only architecture that cannot satisfy strict data residency requirements.
This guide compares ten New Relic alternatives – CubeAPM, Datadog, Dynatrace, Grafana Cloud, Elastic APM, Splunk, Sentry, Honeycomb, IBM Instana, and Coralogix – across pricing, OpenTelemetry support, deployment model, and real-world migration feasibility. Each estimate includes the cloud egress fees most comparison guides ignore.
Pricing Methodology
| Assumption | Value |
|---|---|
| Monthly ingestion | 30TB (~20TB logs, 7TB traces, 3TB metrics) |
| Retention | 30 days, all signals |
| Log indexing | 30% indexed, 70% archive |
| Hosts | 100 |
| Users | 20 full-platform |
| Metric series | 500,000 active |
| Scope | Core observability only |
Estimates are directional, based on public rate cards as of early 2026. Vendor discounts can reduce SaaS costs significantly.
What to Look For in a New Relic Alternative
- Pricing model and cost predictability: How pricing behaves as telemetry volume grows, more users need access, and more features are used. GB-based, seat-based, and host-based pricing produce very different bills at scale.
- OpenTelemetry support – native vs bolt-on: OTel-native platforms ingest OTLP data without transformation. Platforms that added OTel as a layer on top of proprietary agents often require workarounds or charge extra for OTel metrics.
- Deployment model: SaaS-only, self-hosted, or hybrid. For regulated industries, this is the deciding factor before any other evaluation begins.
- Observability depth (MELT coverage): Metrics, Events, Logs, and Traces. Whether each platform covers all four and how well signals correlate for investigation.
- Kubernetes and cloud-native support: Where observability complexity grows fastest – pod-level visibility, service mesh support, and resource-aware dashboards.
- The hidden egress cost: When you send telemetry to any external SaaS platform, your cloud provider charges ~$0.10/GB for data leaving your VPC. At 30TB/month, that is $3,000/month, which does not appear on your observability invoice. Self-hosted platforms avoid this entirely.
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
Overview
CubeAPM is a self-hosted, OpenTelemetry-native, full-stack observability platform that runs inside your own AWS, GCP, or Azure VPC. Traces, logs, and metrics never leave your infrastructure boundary. CubeAPM handles upgrades, patches, and platform operations – you provide the infrastructure.
Ranked in the top 10 APM platforms in G2’s Spring 2026 APM Grid Report. Capterra 5/5, G2 5/5, and #4 easiest-to-use APM tools on G2. SOC 2 Type II and ISO 27001 certified. Used by Policybazaar (insurance), Delhivery ($3.5B logistics – 75% savings after replacing three separate monitoring tools), Mamaearth ($1.2B), world’s largest bus aggregator – redBus (part of MakeMyTrip Limited (NASDAQ: MMYT), 8+ countries), Ola, and Practo (healthcare).
Key Features
- Full MELT observability: APM, logs, infrastructure, Kubernetes, Kafka monitoring, RUM, synthetic monitoring, and error tracking in one platform
- OpenTelemetry-native: Compatible with OpenTelemetry, Datadog, New Relic, Elastic, and Prometheus agents for incremental migration
- Self-hosted, vendor-managed: Zero cloud egress cost (saves ~$3,000/month at 30TB vs any external SaaS). Your monitoring stays up even if the internet doesn’t.
- AI-based Smart Sampling: Retains traces that matter while reducing storage overhead
- Unlimited retention: Included in pricing – no separate retention charges
- MCP server: CubeAPM provides an MCP server that customers can use to query CubeAPM in natural language
- 800+ integrations: Kubernetes, synthetic monitoring, RUM, and error tracking included
Pricing
Ingestion-based, predictable pricing of $0.15/GB. No per-user fees. No per-host charges. Unlimited users and unlimited data retention included.
At 30TB/month: ~$5,100/month all-in ($4,500 license + ~$600 infra)
Delhivery: 75% savings after replacing three separate monitoring tools. Mamaearth: ~70% savings, migrated in under an hour. redBus: 4x faster dashboards, 50% faster MTTR.
“Dashboards are astonishingly fast compared to New Relic – the migration process was also super smooth.”
Direct engineering support via WhatsApp and Slack channels – responds in minutes during incidents.
Cons
- Requires self-hosted deployment in cloud or on-prem; may not suit teams looking for a SaaS-only model.
- AI/ML anomaly detection is growing but not as mature as Dynatrace Davis AI.
- SSO/RBAC less mature than enterprise SaaS incumbents
2. Datadog
Best for: Broad SaaS ecosystem coverage with the budget to manage billing complexity
Overview
Datadog is the largest commercial observability platform and New Relic’s most direct competitor. Its integration catalog (900+) and feature breadth are unmatched – APM, logs, security, RUM, synthetics, and network monitoring under one roof. The trade-off is cost: host-based pricing compounds quickly at scale, and custom metrics charges are a persistent source of bill shock. OTel metrics are often billed as custom metrics.
Key Features
- Unified observability: metrics, logs, APM, RUM, synthetics, security, database monitoring
- 900+ integrations – largest ecosystem in the category
- Kubernetes Explorer with pod, deployment, and resource visibility
- Watchdog AI for proactive anomaly detection
Pricing
Multi-dimensional billing: hosts + custom metrics + log ingestion ($0.10/GB) + log indexing (~$1.70/million events) + APM spans + RUM sessions.
At 30TB/month: ~$30,000-$45,000+/month
Log indexing is the dominant cost driver. Self-hosted platforms with per-GB pricing avoid the multi-dimensional billing that makes Datadog costs difficult to forecast.
Cons
- Billing complexity: host fees + custom metric overages + log indexing combine unpredictably.
- OTel metrics billed as custom metrics – adds cost for teams adopting open standards.
- SaaS-only; not suitable for data residency requirements
- Total cost at scale significantly exceeds alternatives with simpler pricing models.
3. Dynatrace
Best for: Large enterprises that need AI-automated root cause analysis
Overview
Dynatrace differentiates with its Davis AI engine, which automatically maps service dependencies and performs causal root-cause analysis. Gartner ranks Dynatrace highest in “Ability to Execute” among observability vendors. The platform targets large enterprises with complex microservice estates. OneAgent provides automatic discovery but creates its own vendor lock-in.
Key Features
- Davis AI: Automatic baselining, anomaly detection, and probable-cause analysis
- Full-stack monitoring via OneAgent with automatic service discovery
- OpenTelemetry support via OTLP API and Dynatrace Collector
- Dedicated Kubernetes observability with Dynatrace Operator
Pricing
Usage-based with separate rate-card units. Full-Stack Monitoring at $0.01/memory-GiB-hour, Log Management at $0.20/GiB.
At 30TB/month: ~$20,000-$35,000+/month
Cons
- Proprietary OneAgent creates its own vendor lock-in.
- Memory-GiB-hour pricing is harder to estimate than simple per-GB models.
- Log retention billed separately from log ingestion.
- Davis AI requires a baselining period before delivering full value.
4. Grafana Cloud (LGTM Stack)
Best for: OTel-first teams that want flexible dashboards and open-source foundations
Overview
Grafana Labs assembled the LGTM stack – Loki (logs), Grafana (dashboards), Tempo (traces), Mimir (metrics) – into a coherent observability platform. Grafana Cloud is the managed version. Paired with Grafana Alloy (an OTel Collector distribution), it provides dedicated OTLP endpoints. Best for teams already running Prometheus who want to extend to full observability without a forklift migration.
Key Features
- LGTM stack: Mimir for metrics, Loki for logs, Tempo for traces
- Grafana Alloy: OTel Collector distribution with built-in Prometheus pipelines
- Strongest dashboarding and visualization across multiple telemetry sources
- k6 performance testing and cost attribution features
Pricing
Usage-based across telemetry types. Logs: $0.05/GB process + $0.40/GB write + $0.10/GB retain. Metrics: $6.50/1k active series.
At 30TB/month (managed cloud): ~$15,000-$20,000+/month
Self-hosted (OSS) is free but operationally demanding at scale. For teams that need self-hosted observability without the operational overhead, vendor-managed options exist that handle platform operations within your VPC.
Cons
- No native APM out-of-the-box; requires significant configuration.
- Self-hosting at scale requires dedicated SRE expertise.
- Usage-based pricing still grows with volume on managed cloud.
- LGTM stack has a steep learning curve for teams new to Grafana.
5. Elastic APM
Best for: Teams already on the ELK stack who want to add APM without a new vendor
Overview
Elastic APM is the distributed tracing and application monitoring component of the Elastic Stack. For teams already indexing logs in Elasticsearch and visualizing in Kibana, adding APM is natural. Provides distributed tracing, service maps, error tracking, and MELT correlation. The OSS version reached end-of-service in September 2025 – evaluate managed options carefully.
Key Features
- Native Elasticsearch integration: APM data correlates directly with log indices
- OpenTelemetry compatible across serverless, self-managed, and hybrid deployments
- ML-based anomaly detection via Elastic ML
- Self-hosted (SSPL license) or Elastic Cloud deployment
Pricing
Self-hosted is free; you cover infrastructure. Elastic Cloud: consumption-based. Logs Essentials from $0.07/GB ingested.
At 30TB/month (Elastic Cloud): ~$8,000-$15,000/month
Cons
- Significant operational overhead to run self-hosted at scale
- Kibana Query Language (KQL) is less developer-friendly than SQL.
- 2021 SSPL licensing change – review for open-source compliance
- APM experience is less polished than purpose-built APM tools.
6. Splunk Observability Cloud
Best for: Teams already invested in the Splunk ecosystem who need unified observability + security
Overview
Splunk Observability Cloud provides real-time, full-fidelity monitoring using the Splunk Distribution of the OTel Collector. Deep integration with Splunk SIEM makes it strong for teams that need correlated observability and security workflows. The trade-off: it is the most expensive platform in this comparison.
Key Features
- Real-time, full-fidelity monitoring with no default sampling
- Splunk Distribution of OTel Collector for instrumentation
- Deep Splunk SIEM integration for security-correlated observability
- Modular packaging for infra, APM, RUM, and synthetics
Pricing
Modular with separate packaging. Infrastructure from $15/host/month. End-to-End from $75/host/month.
At 30TB/month: ~$35,000-$60,000+/month
The highest cost in this comparison. Teams running ingestion-based pricing models at the same volume pay a fraction of this amount.
Cons
- Most expensive platform in this comparison by a significant margin
- Modular pricing makes forecasting difficult.
- Primary value comes with existing Splunk investment – less compelling standalone.
- SaaS-first, not suitable for self-hosted requirements
7. Sentry
Best for: Developer-first teams that debug from code and user experience inward
Overview
Sentry is a developer-first error monitoring platform that has grown into broader application monitoring: errors, tracing, logs, session replay, profiling, and cron monitoring. Session Replay provides video-like reproductions of user sessions – a meaningful advantage not available in most observability platforms.
Key Features
- Session Replay: Video-like reproductions of user sessions for web and mobile
- Error monitoring with stack traces, breadcrumbs, and context
- Distributed tracing and performance monitoring
- Self-hosted option available
Pricing
Event + usage-based. Team plan from $26/month base. Logs: $0.50/GB.
At 30TB/month: ~$15,260/month
Cons
- Primarily error and debugging focused – not full infrastructure observability
- Teams needing deep infrastructure monitoring will need a complementary tool.
- Pricing at high volume can approach traditional APM costs.
- Less suited for infra-first or SRE-led observability workflows
8. Honeycomb
Best for: High-cardinality event debugging and OTel-first distributed tracing
Overview
Honeycomb stores wide events and derives trace, log, and metric views from a single data model. This makes it exceptionally powerful for debugging high-cardinality distributed systems where traditional APM sampling loses the signal. Honeycomb is OpenTelemetry-first, with OTel as the primary instrumentation standard. A private cloud option was announced in November 2025 for teams with data residency needs.
Key Features
- OpenTelemetry-first: OTel is the primary and recommended instrumentation standard
- Wide events data model: Stores rich, high-cardinality events and derives all views
- BubbleUp: Automated outlier detection across telemetry dimensions
- Unified telemetry: traces, logs, and metrics navigated in one workflow
Pricing
Usage-based, starts at $0.10/GB ingested.
At 30TB/month: ~$5,600/month (range $5K-$24K depending on event volume)
Cons
- Primarily tracing and debugging; infrastructure monitoring is not the core strength.
- SaaS-only (private cloud option announced November 2025 but still early)
- Dashboard-first teams may find Honeycomb’s workflow different.
- Spend scales with telemetry volume even with clear ingest pricing.
9. IBM Instana
Best for: Enterprises with complex hybrid and multi-cloud environments
Overview
IBM positions Instana as full-stack observability powered by agentic AI. Automatic service discovery and dependency mapping across 300+ technologies, real-time visibility with 1-second granularity, and Kubernetes monitoring across pods, containers, and service mesh. Agentic AI incident investigation is in preview.
Key Features
- Automatic service discovery and dependency mapping across 300+ technologies
- Real-time visibility with 1-second granularity
- All OpenTelemetry signals (traces, metrics, logs) generally available
- Synthetic monitoring with managed global points of presence
Pricing
Licensed by Managed Virtual Server (MVS). Minimum 10 hosts. Unlimited users. Logs from $0.35/GB. Fair-use: 325 GB/Standard SaaS MVS/month.
At 30TB/month: ~$10,500/month (range $10.5K-$37K)
Cons
- Host-based MVS licensing, not per-GB; cost scales with infrastructure footprint.
- Some AI capabilities still in preview
- Enterprise-oriented; smaller teams may find the platform over-specified.
- Minimum 10-host commitment
10. Coralogix
Best for: Teams that want cost-controlled observability with in-VPC data storage
Overview
Coralogix differentiates with its Streama engine for in-stream processing, which monitors 4x more data at lower cost by analyzing telemetry before indexing. The TCO Cost Optimizer routes critical logs to instant analysis and low-value data to archive. Data is stored in the customer’s S3 bucket with infinite retention. 4,000+ customers including Palo Alto, Adobe, and Monday.com.
Key Features
- Streama engine: In-stream processing reduces indexing costs significantly
- TCO Cost Optimizer: Routes logs by priority – critical to instant, low-value to archive
- DataPrime query engine: Unified querying across logs, metrics, and traces
- 300+ integrations, OpenTelemetry native support, unlimited users and hosts
Pricing
Unit-based ($1.50/unit). Logs $0.42/GB, Traces $0.16/GB, Metrics $0.05/GB. Customer cloud storage with infinite retention.
At 30TB/month: ~$8,000-$14,000/month (varies by signal mix and indexing)
Cons
- DataPrime is a proprietary query language (not PromQL/SQL).
- Unit-based pricing requires upfront planning.
- Not fully self-hosted; SaaS control plane with customer-owned storage
- SOC 2 Type II, ISO 27001, GDPR, HIPAA compliant but control plane remains SaaS.
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) |
| Datadog | ~$30K-$45K+ | Host + feature-based | Partial* | SaaS only | No |
| Dynatrace | ~$20K-$35K+ | GiB-hour + commit | Partial | Managed option | Managed |
| Grafana Cloud | ~$15K-$20K+ | Usage-based | Native | If self-hosted | Yes |
| Elastic APM | ~$8K-$15K | Deployment-based | Partial | If self-hosted | Yes |
| Splunk | ~$35K-$60K+ | Host + module-based | Partial | SaaS only | No |
| Sentry | ~$15K-$32K | Event + usage | Partial | If self-hosted | Yes |
| Honeycomb | ~$5K-$24K | Usage-based | Native | Limited | Limited |
| IBM Instana | ~$10.5K-$37K | Host (MVS)-based | Partial | If self-hosted | Yes |
| Coralogix | ~$8K-$14K | Unit-based | Partial | Customer S3 | Hybrid |
| New Relic (ref.) | ~$20K-$25K+ | Ingest + per-user | Partial | SaaS only | No |
* OTel metrics in Datadog are often billed as custom metrics. New Relic included as reference. All estimates use the methodology assumptions above. Vendor discounts and EDP commitments can significantly reduce SaaS costs.
What New Relic Actually Costs at Your Team Size
Most comparison guides show pricing tiers. What they do not show is how those tiers combine – data ingest + user seats + synthetics + cloud egress – into a real monthly bill.
| Team Profile | Data / Users | New Relic /mo | CubeAPM /mo | Annual Saving | Saving % |
|---|---|---|---|---|---|
| Small team | 500 GB, 3 users | ~$458 | ~$75 | ~$4,596/yr | ~84% |
| Growing team | 5 TB, 10 users | ~$4,955 | ~$750 | ~$50,460/yr | ~85% |
| Mid-market | 30 TB, 50 users | ~$24,745 | ~$4,500 | ~$242,940/yr | ~82% |
| Enterprise | 200 TB, 150 users | ~$97,750 | ~$30,000 | ~$813,000/yr | ~69% |
New Relic costs: Standard plan, Original data ($0.40/GB beyond 100GB free), full platform users at $99 to $349 per user per month for full platform access. CubeAPM: $0.15/GB, no user fees. Enterprise pricing may include negotiated discounts not reflected here.
If you want to model your current New Relic bill before committing to a switch, the New Relic pricing calculator breaks down every cost dimension: data ingest, user seats, synthetics, and cloud egress fees most teams overlook.
The Hidden Cost: Cloud Data-Out Egress
When you send telemetry to any external SaaS platform – New Relic, Datadog, or any cloud-hosted alternative – your cloud provider charges approximately $0.10/GB for data leaving your VPC. At 30TB/month, that is $3,000/month in AWS or GCP egress fees, which does not appear on your observability invoice. Self-hosted platforms running inside your VPC have zero data-out cost.
How to Migrate from New Relic to an OTel-Native Platform
Migration anxiety is real – you have built dashboards, tuned alerts, and accumulated operational knowledge in New Relic over months or years. The good news: switching to an OpenTelemetry-native platform is structurally less painful than previous APM migrations. Once your services emit OTLP data, you can point that data at any compatible backend with a configuration change rather than re-instrumentation.
| Week | Focus | Key Actions | Exit Criteria |
|---|---|---|---|
| 1 | Instrument inventory | List every service using NR agents. Map data volumes per service. Choose target platform. | Full inventory. Platform selected. |
| 2 | Parallel run | Deploy OTel Collector alongside NR agents on 1-2 non-critical services. Dual-write telemetry. Compare dashboards. | Traces/metrics parity confirmed on pilot services. |
| 3 | Dashboard migration | Recreate top 10 critical dashboards and all active alerts. Validate alert accuracy. Remove NR agents from pilot services. | Critical dashboards live. Alert parity verified. |
| 4 | Full cutover | Roll OTel agents to remaining services. Cancel NR agents service-by-service. Run NR in read-only mode for 2 weeks. | All services on new platform. NR agents decommissioned. |
Practical note: Run both platforms simultaneously for at least two weeks before cancelling New Relic. Teams consistently discover dashboards they forgot existed, alerts that were silently firing, or integrations that depended on NR’s API. Document what each dashboard is measuring, not the NRQL syntax, before migrating.
Which New Relic Alternative Is Right for Your Use Case?
- Choose CubeAPM if cost predictability and data sovereignty are priorities. Ingestion-based pricing of $0.15/GB, unlimited users, runs in-VPC with zero egress cost.
- Choose Datadog if you need the broadest SaaS ecosystem and your budget supports host-based pricing at scale. Model custom metrics costs before committing.
- Choose Dynatrace if enterprise AI automation and causal root-cause analysis are your primary needs. Be prepared for the annual commitment.
- Choose Grafana Cloud if you are OTel-first, want flexible dashboards, and are comfortable managing or funding the LGTM stack.
- Choose Elastic APM if your team already runs ELK and wants to add distributed tracing without introducing another vendor.
- Choose Splunk if you are already invested in the Splunk ecosystem and need correlated observability and security workflows.
- Choose Sentry if your team is developer-led, debugging from code inward, and needs session replay more than infrastructure monitoring.
- Choose Honeycomb if high-cardinality event debugging and distributed tracing with an OTel-first workflow are your primary needs.
- Choose IBM Instana if you run complex hybrid or multi-cloud environments and need automatic discovery across 300+ technologies.
- Choose Coralogix if you want cost-controlled observability with data stored in your own S3 bucket and in-stream processing.
When New Relic Is Still the Better Choice
New Relic is still the right choice for teams that want a broad commercial observability platform with strong full-stack coverage in one SaaS environment.
- If the free tier offering 100GB free per month is sufficient for your use case.
- You want one vendor covering APM, infrastructure, browser, synthetics, Kubernetes, and incident workflows in one place.
- You are already heavily invested in the New Relic ecosystem (dashboards, alerts, NRQL queries) and migration cost exceeds the pricing delta.
- You need native OTLP ingest inside a commercial SaaS platform without moving to a self-managed stack.
- You need mature synthetic monitoring with scripted browser/API tests and private locations.
- You are comfortable actively managing telemetry volume, CCU consumption, and ingest governance.
- You want AI-assisted observability (New Relic AI, alert-coverage analysis) built natively into the platform.
Final Thoughts
There is no single best New Relic alternative for every team. The right choice in 2026 depends on what matters most: pricing clarity, deployment model, OpenTelemetry fit, Kubernetes visibility, or day-two operational effort.
If compliance or data residency is a hard requirement, self-hosted platforms are the only viable path – most SaaS alternatives do not solve this structurally. If cost is the primary driver, model your bill across data volume, user count, and cloud egress before committing – the gap between GB-based pricing and multi-dimensional billing models is often larger than teams expect. If enterprise automation is the priority, the AI-led platforms justify their premium for complex environments. If high-cardinality debugging matters most, newer OTel-first platforms offer a fundamentally different investigation model. And if your team is already embedded in a specific ecosystem – Elastic, Splunk, or Grafana – extending that stack is often the lowest-friction path.
Compare your top two or three options against your actual telemetry volume, deployment needs, and budget before making the switch. The numbers at your scale will make the decision clearer than any feature matrix.
Frequently Asked Questions
- What is the best New Relic alternative in 2026?
There is no single best option for every team. For cost predictability and data sovereignty, self-hosted OTel-native platforms offer the strongest structural advantages. Datadog for the broadest SaaS ecosystem. Dynatrace for enterprise AI automation. Grafana for dashboards and OpenTelemetry flexibility. Honeycomb for high-cardinality distributed tracing. Sentry for developer-first error monitoring.
- Which New Relic alternative is best for self-hosting?
Grafana (LGTM stack), Elastic APM, and Sentry support fully self-managed deployment. IBM Instana and Coralogix offer hybrid options. For teams that want self-hosted observability without managing the backend themselves, vendor-managed self-hosted options exist that handle platform operations within your VPC.
- Is Datadog better than New Relic?
Not across the board. Datadog has the largest integration ecosystem and strongest cloud-native monitoring breadth. New Relic remains strong for teams that want broad observability with native OTLP ingest and a mature commercial platform. Both are significantly more expensive than OTel-native alternatives at the same data volume.
- What is the cheapest New Relic alternative?
For teams below the free tier (1 user + 100GB/month), New Relic’s free tier is hard to beat. Beyond that, platforms with predictable per-GB pricing and no per-user fees offer the lowest TCO at most team sizes – particularly when cloud egress savings are included in the calculation.
- Can I use OpenTelemetry to replace New Relic agents?
Yes, and this is the recommended migration path. New Relic’s proprietary agents can be replaced with the OTel SDK for your language and the OTel Collector for batching and routing. New Relic itself accepts OTLP data, so you can migrate instrumentation to OTel without changing backends first – then point the Collector at your new platform when ready.
- What happens to my data when I cancel New Relic?
New Relic retains your data according to your plan’s retention period after cancellation (8 days on Original plan, 90 days on Data Plus). After that, the data is deleted. Running your new platform in parallel for 2-4 weeks before cancelling is important.
