Top 7 New Relic Alternatives With OpenTelemetry-Native Support

OpenTelemetry-Native Options for Modern Infrastructure

OpenTelemetry is becoming the default instrumentation layer for modern observability. Teams adopting OTel expect their backend to ingest OTLP data natively – without transformation penalties, custom metrics surcharges, or proprietary agent dependencies. New Relic accepts OTLP data, but its pricing model still charges $49 to $349/month for full platform access per user, and its core platform was built around proprietary agents and NRQL – a non-portable query language that locks dashboards and alerts to the platform.

For teams building on OpenTelemetry, the backend should be a configuration change – not a re-instrumentation project. This guide evaluates seven alternatives through the OTel lens: how deeply each platform supports OpenTelemetry, whether it introduces hidden costs for OTel-sourced telemetry, and how cleanly it fits into a Collector-based pipeline.

The seven tools covered:

• CubeAPM – self-hosted, OTel-native, vendor-managed
• Honeycomb – OTel-first event debugging
• Grafana Cloud – LGTM stack with Alloy OTel Collector
• Elastic APM – OTel-compatible on the Elastic Stack
• Coralogix – OTel-native with customer-owned storage
• Dynatrace – enterprise AI with OTLP API support
• Sentry – developer-first with partial OTel trace support

*Estimates based on 30TB/month ingestion, 100 hosts, 20 users, 30-day retention. Based on public rate cards, early 2026.*

What Makes an Observability Platform Truly OTel-Native?

Most vendors now list OpenTelemetry compatibility on their feature pages. But compatibility is not the same as native support. The practical differences show up in how the platform handles OTel data once it arrives:

• Native OTLP ingest: Does the platform accept OTLP (gRPC/HTTP) as a first-class data path, or does it translate OTel signals into a proprietary format?
• No OTel metrics penalty: Some platforms bill OTel-sourced metrics as custom metrics – adding cost for teams adopting open standards. True OTel-native platforms treat OTel data the same as agent-sourced data.
• Collector-based architecture: Can you run a standard OTel Collector (or vendor distribution) as the single telemetry pipeline, or does the platform require a proprietary agent alongside the Collector?
• Vendor portability: If your instrumentation is OTel SDK-based and your pipeline runs through the Collector, switching backends is a configuration change. Platforms that require proprietary SDKs or query languages erode this portability.
• Deployment model: For regulated teams, SaaS-only platforms introduce cloud egress costs (~$0.10/GB, which adds $3,000/month at 30TB) and potential data residency complications. Self-hosted or customer-storage options avoid both.

OpenTelemetry Support Depth: Feature Matrix

Not all OTel support is created equal. This matrix compares how each platform handles OpenTelemetry data across five practical dimensions:

Tool	Native OTLP Ingest	OTel Collector Support	Proprietary Agent Required	OTel Metrics Penalty	Migration Path from NR
CubeAPM	Yes – native	Yes + DD/NR/Elastic/Prom agents	No	None	Config change; under an hour
Honeycomb	Yes – native	Yes (primary path)	No	None	Collector swap
Grafana Cloud	Yes – native	Yes (Alloy distro)	No	None	Collector swap
Elastic APM	Yes	Yes + Elastic Agent	Optional	None	Dual-write parallel
Coralogix	Yes	Yes	No	None	Collector swap
Dynatrace	Via OTLP API	Via Dynatrace Collector	OneAgent recommended	Possible*	Parallel run required
Sentry	Partial (traces)	Limited	Sentry SDK	N/A	SDK migration
New Relic (ref.)	Yes (OTLP)	Yes	NR agent recommended	None	–

* Dynatrace may bill some OTel-sourced metrics differently depending on configuration and commitment tier. New Relic included as reference.

1. CubeAPM

Best for: OTel-native teams that want full-stack observability inside their own VPC with predictable pricing

Overview

CubeAPM is a self-hosted, OpenTelemetry-native, full-stack observability platform. It accepts OTLP data natively – traces, metrics, and logs flow through the OTel Collector directly into CubeAPM without format conversion or proprietary agent requirements. The platform runs inside your AWS, GCP, or Azure VPC; telemetry never leaves your infrastructure boundary. CubeAPM handles upgrades, patches, and platform operations.

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. 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). SOC 2 Type II and ISO 27001 certified.

OTel Integration

• OpenTelemetry-native from day one: Built on OTel – no proprietary agent, no translation layer
• Multi-agent compatibility: Compatible with OpenTelemetry, Datadog, New Relic, Elastic, and Prometheus agents for incremental migration
• No OTel metrics penalty: OTel-sourced metrics are treated identically to any other signal – no custom metrics surcharge
• Collector-native pipeline: Standard OTel Collector routes all signals directly to CubeAPM

Key Features

• Full MELT observability: APM, logs, infrastructure, Kubernetes, Kafka monitoring, RUM, synthetic monitoring, and error tracking
• 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.

Pros

• OTel-native from the ground up – zero proprietary agent dependency
• 70-75% lower cost than enterprise APM at scale
• Complete data ownership – telemetry never leaves your VPC
• Zero cloud egress cost
• Fast migration – multiple customers report under an hour setup

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. Honeycomb

Best for: High-cardinality event debugging with an OpenTelemetry-first workflow

Overview

Honeycomb was designed around OpenTelemetry from the start. It stores wide, high-cardinality events and derives trace, log, and metric views from a single data model. This makes it exceptionally effective for debugging distributed systems where traditional APM sampling loses the signal. OTel is the primary and recommended instrumentation standard – not a bolt-on compatibility layer.

OTel Integration

• OpenTelemetry-first: OTel is the primary instrumentation path, not an alternative to a proprietary SDK
• Native OTLP ingest: gRPC and HTTP endpoints with no format translation
• No metrics penalty: All OTel-sourced signals treated as first-class data
• Wide event model: Preserves full OTel span attributes for high-cardinality analysis

Key Features

• BubbleUp: Automated outlier detection across telemetry dimensions
• Unified telemetry: Traces, logs, and metrics navigated in one workflow
• Private cloud option announced November 2025 for data residency

Pricing

Usage-based, starts at $0.10/GB ingested.

At 30TB/month: ~$5,600/month (can range $5K-$24K depending on event volume and plan)

Pros

• Strongest OpenTelemetry-first product direction in the market
• Exceptional for distributed tracing and high-cardinality debugging
• Unified navigation across traces, logs, and metrics

Cons

• Primarily a tracing and debugging platform – infrastructure monitoring is not the core strength.
• SaaS-only (private cloud option still early)
• Dashboard-first teams may find the investigation workflow different from traditional APM.

3. 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 unified observability platform. Grafana Cloud is the managed version. Paired with Grafana Alloy, which is an OpenTelemetry Collector distribution, it provides dedicated OTLP endpoints that auto-route signals to the right backend. For teams already invested in Prometheus, Alloy extends that foundation to full OTel-native observability without a forklift migration.

OTel Integration

• Grafana Alloy: A dedicated OTel Collector distribution with built-in Prometheus pipelines
• Native OTLP endpoints: Auto-route traces to Tempo, metrics to Mimir, logs to Loki
• No OTel metrics penalty: OTel-sourced metrics treated the same as Prometheus-scraped metrics
• Self-hosted path: Full LGTM stack is open source – teams can run it on their own infrastructure. Self-hosted platforms like CubeAPM offer a simpler operational model for teams that want in-VPC deployment without managing the backend stack themselves.

Key Features

• Strongest dashboarding and visualization across multiple telemetry sources
• k6 performance testing integrated into the observability ecosystem
• Cost attribution features for metrics, logs, and traces

Pricing

Usage-based. Logs: $0.05/GB process + $0.40/GB write + $0.10/GB retain. Traces: same structure. Metrics: $6.50/1k active series. Platform fee: $19/month.

At 30TB/month (managed cloud): ~$15,000-$20,000+/month

Pros

• Fully OTel-native through the Alloy Collector distribution
• Adaptive Metrics/Logs actively help reduce billing
• Strong open-source community; highly customizable

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.

4. Elastic APM

Best for: Teams on the Elastic Stack that want OTel-compatible APM without a new vendor

Overview

Elastic APM is the distributed tracing and application monitoring component of the Elastic Stack. OpenTelemetry support spans serverless, self-managed, and hybrid deployments. For teams already indexing logs in Elasticsearch and visualizing in Kibana, adding OTel-compatible APM is a natural extension. 

Note: the OSS version reached end-of-service in September 2025.

OTel Integration

• OTLP ingest: Accepts OpenTelemetry data across all deployment models
• Elastic Agent optional: OTel Collector can send data directly, though Elastic Agent adds fleet management
• No OTel metrics penalty: OTel-sourced signals are not charged differently
• Self-hosted OTel path: Run Elastic APM self-managed with OTel Collector as the primary pipeline

Key Features

• Distributed tracing, service maps, and error tracking correlated with log indices
• Machine learning-based anomaly detection via Elastic ML
• RUM via JavaScript agent for frontend monitoring
• Available self-hosted (SSPL license) or Elastic Cloud

Pricing

Self-hosted is free; you cover infrastructure. Elastic Cloud: consumption-based. Serverless Observability: Logs Essentials from $0.07/GB ingested.

At 30TB/month (Elastic Cloud): ~$8,000-$15,000/month

Pros

• Zero incremental cost if already running Elastic for logs
• Strong log + trace correlation in the same query interface
• Self-hosted option keeps data on your infrastructure

Cons

• Significant operational overhead to run self-hosted at scale
• 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 platforms.

5. Coralogix

Best for: Teams that want OTel-native observability with cost-controlled, customer-owned storage

Overview

Coralogix takes a different approach to observability costs: its Streama engine processes telemetry in-stream, which lets teams monitor up to 4x more data at the same cost by routing critical logs to instant analysis and low-value data to archive. Data is stored in the customer’s own S3, Azure Blob, or GCS bucket – providing a data residency model closer to self-hosted platforms than traditional SaaS.

OTel Integration

• OpenTelemetry native: 300+ integrations with native OTel support across all signal types
• Standard OTel Collector: No proprietary agent required for OTel-based pipelines
• Customer-owned storage: Telemetry lands in your cloud storage bucket with infinite retention – partial data sovereignty without full self-hosting

Key Features

• TCO Cost Optimizer: Routes critical logs to instant analysis, low-value to archive
• DataPrime query engine: Unified querying across logs, metrics, and traces
• APM, RUM, log analytics, infrastructure monitoring, and SIEM
• Unlimited users, unlimited hosts, unlimited data sources

Pricing

Unit-based ($1.50/unit). Logs $0.42/GB, Traces $0.16/GB, Metrics $0.05/GB.

At 30TB/month: ~$8,000-$14,000/month (varies by signal mix and indexing tier)

Pros

• Customer-owned storage provides data control without full self-hosting.
• Streama engine can materially reduce costs for high-volume teams.
• Unlimited users and hosts included – no seat tax
• SOC 2 Type II, ISO 27001, GDPR, HIPAA, PCI DSS compliant

Cons

• DataPrime is a proprietary query language (not PromQL or SQL).
• Unit-based pricing requires upfront capacity planning.
• Not fully self-hosted – SaaS control plane with customer-owned storage. Teams needing full in-VPC deployment should evaluate fully self-hosted alternatives.

6. Dynatrace

Best for: Large enterprises that need AI-automated root cause analysis across complex estates

Overview

Dynatrace differentiates with Davis AI – automatic baselining, anomaly detection, and causal root-cause analysis that reduces alert fatigue in large microservice environments. Gartner ranks Dynatrace highest in “Ability to Execute” among observability vendors. The platform supports OTLP ingest via API and Dynatrace Collector, but its core architecture centers on the proprietary OneAgent.

OTel Integration

• OTLP API: Accepts OpenTelemetry traces, metrics, and logs via OTLP endpoints
• Dynatrace Collector: A vendor Collector distribution for OTel-based pipelines
• OneAgent dependency: Full Davis AI capabilities require OneAgent – OTel-only deployments may not get the same automatic discovery and topology mapping
• Potential metrics treatment: Depending on configuration, OTel-sourced metrics may be handled differently than OneAgent-sourced data

Key Features

• Davis AI: Automatic baselining, anomaly detection, and probable-cause analysis
• Full-stack monitoring via OneAgent with automatic service discovery
• Dedicated Kubernetes observability with flexible deployment via Dynatrace Operator
• Managed deployment option for data residency (Dynatrace Managed)

Pricing

Usage-based with separate rate-card units. Full-Stack Monitoring at $0.01/memory-GiB-hour, Log Management ingest at $0.20/GiB.

At 30TB/month: ~$20,000-$35,000+/month

Pros

• Best automated root cause analysis in the market
• Automatic full-topology discovery – minimal manual configuration
• Managed deployment option for data residency
• Strong compliance and enterprise security features

Cons

• OneAgent creates its own vendor lock-in – the opposite of the OTel portability promise.
• Memory-GiB-hour pricing is harder to estimate than simple per-GB models.
• Log retention billed separately from log ingestion
• OTel-only deployment does not unlock the full Davis AI experience.

7. Sentry

Best for: Developer-first teams that need error monitoring and session replay more than infrastructure observability

Overview

Sentry is a developer-first monitoring platform covering errors, tracing, logs, session replay, profiling, and cron monitoring. Its OTel support is narrower than full observability platforms – primarily focused on distributed tracing via OTel SDK integration. For teams that debug from code and user experience inward rather than infrastructure outward, Sentry fills a different gap than traditional APMs.

OTel Integration

• Partial OTel support: Sentry supports OpenTelemetry traces via SDK integration, but logs and metrics follow the Sentry SDK path
• Sentry SDK primary: The Sentry SDK remains the primary instrumentation method – OTel is supplementary, not the core pipeline
• Limited Collector support: Not designed as a Collector-based backend in the way full OTel-native platforms are

Key Features

• Session Replay: Video-like reproductions of user sessions – not available in most observability platforms
• 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 (Team PAYG).

At 30TB/month: ~$15,260/month

Pros

• Best-in-class developer experience for error triage
• Session Replay provides debugging capabilities not found in traditional APM.
• Self-hosted option for data control

Cons

• OTel support limited primarily to traces – not a full OTel-native backend
• Primarily error and debugging focused – not full infrastructure observability
• Teams needing deep infrastructure monitoring will need a complementary tool.
• Less suited for infra-first or SRE-led observability workflows

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)
Honeycomb	~$5K-$24K	Usage-based	Native	Limited	Limited
Grafana Cloud	~$15K-$20K+	Usage-based	Native	If self-hosted	Yes
Elastic APM	~$8K-$15K	Deployment-based	Partial	If self-hosted	Yes
Coralogix	~$8K-$14K	Unit-based	Yes	Customer storage	Partial
Dynatrace	~$20K-$35K+	GiB-hour + commit	Partial	Managed option	Managed
Sentry	~$15K-$32K	Event + usage	Partial	If self-hosted	Yes
New Relic (ref.)	~$20K-$25K+	Ingest + per-user	Partial	SaaS only	No

* Dynatrace OTel metrics treatment may vary by configuration. New Relic included as reference. All estimates directional, based on public rate cards, early 2026. Vendor discounts can reduce SaaS costs significantly.

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, 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

Switching to an OpenTelemetry-native backend is structurally simpler than previous APM migrations. Once your services emit OTLP data through the OTel Collector, pointing that data at a new backend is a Collector configuration change – not a re-instrumentation project.

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 Alternative Fits Your OTel Strategy?

• Choose CubeAPM if you want OTel-native observability inside your VPC with predictable $0.15/GB pricing, zero egress cost, and no proprietary agent dependency.
• Choose Honeycomb if your team prioritizes high-cardinality event debugging and wants the strongest OTel-first investigation workflow in the market.
• Choose Grafana Cloud if you are building on Prometheus/OTel and want the Alloy Collector distribution with the most flexible dashboarding in the category.
• Choose Elastic APM if your team already runs the Elastic Stack and wants OTel-compatible APM without introducing another vendor.
• Choose Coralogix if you need OTel-native observability with customer-owned storage and cost optimization through in-stream processing.
• Choose Dynatrace if enterprise AI automation and causal root-cause analysis outweigh OTel portability concerns. Be prepared for OneAgent dependency.
• Choose Sentry if your team is developer-led and needs session replay and error monitoring more than full OTel-native infrastructure observability.

When New Relic Is Still the Better Choice

New Relic remains the right choice for teams that value a broad commercial platform with native OTLP ingest inside a 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.
• You are already heavily invested in the NR ecosystem (dashboards, alerts, NRQL) and migration cost exceeds the pricing delta.
• You need mature synthetic monitoring with scripted browser/API tests and private locations.
• You want AI-assisted observability built natively into the platform.

Final Thoughts

OpenTelemetry has shifted how teams should evaluate observability backends. When your instrumentation is OTel SDK-based and your pipeline runs through the Collector, the backend becomes interchangeable – the question is no longer which platform supports OTel, but how deeply it supports OTel without introducing proprietary dependencies, custom metrics penalties, or lock-in through query languages and agents.

The platforms in this guide sit on a spectrum. On one end, fully OTel-native backends treat the Collector as the primary data path and charge predictably for what you ingest. On the other end, enterprise platforms have added OTLP endpoints on top of proprietary architectures – the OTel data gets in, but the full platform experience still depends on a vendor-specific agent. Neither approach is universally wrong; the right choice depends on where your team sits on the portability-versus-automation spectrum.

For teams building new observability stacks, OTel-native platforms avoid accumulating the same vendor lock-in that made leaving New Relic painful in the first place. For teams with complex, fast-moving estates that need AI-driven automation today, the enterprise platforms justify their agent dependency with operational value. Compare your top two options against your actual telemetry volume, OTel maturity, and deployment requirements before committing.

Frequently Asked Questions

1. What makes a platform truly OpenTelemetry-native versus just OTel-compatible?

An OTel-native platform was built to accept OTLP data as its primary ingest path – no format translation, no proprietary agent requirement, and no custom metrics surcharge for OTel-sourced signals. OTel-compatible platforms accept OTLP data but may require a proprietary agent for full functionality or bill OTel metrics differently.

2. Does New Relic support OpenTelemetry?

New Relic accepts OTLP data and recommends it as a preferred ingest method. However, the platform was built around proprietary agents and NRQL, and its pricing model charges per user on top of per-GB – a structure that does not change based on instrumentation method.

3. Which New Relic alternative is best for self-hosting with OTel?

Grafana (LGTM stack) and Elastic APM support fully self-managed deployment with OTel Collector pipelines. 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.

4. Can I migrate from New Relic to an OTel-native platform without downtime?

Yes. The standard approach is to deploy the OTel Collector alongside existing NR agents, dual-write telemetry to both platforms during a parallel run, then point the Collector exclusively at the new backend once parity is confirmed. Most teams complete this in 2-4 weeks.

5. Do OTel-native platforms cost less than New Relic?

Generally yes at mid-to-enterprise scale. Platforms with per-GB pricing and no user fees avoid New Relic’s dual cost axis (data + seats). At 30TB/month, the cost gap ranges from 60% to 85% depending on the alternative. Self-hosted options additionally eliminate ~$3,000/month in cloud egress fees.

6. What happens to my NRQL dashboards when I switch?

NRQL is proprietary and non-portable. Every dashboard and alert must be rebuilt in the new platform. This is why documenting what each dashboard measures (not the NRQL syntax) is a critical early step in any migration.