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REMS vs New Relic — Detailed Comparison | OpsTree
Comparison Guide

REMS vs
New Relic

New Relic reformed its pricing model and built a solid AI assistant. But NRAI is still passive, your data still lives in their cloud, and the proprietary NRDB makes leaving painful. REMS gives you active AI investigation, full data sovereignty, and zero lock-in.

50–70%
Lower total cost
Unlimited
Data retention
Active AI
vs Passive NRAI
Zero
Vendor lock-in
Feature Comparison

REMS vs New Relic at a glance

Every dimension that matters — cost, AI, privacy, flexibility, and ease of use.

Capability
by OpsTree
Competitor
Data stays in your VPC Always — fully self-hosted Never — SaaS only
Pricing model Infra cost only GB ingest + user seats
Active AI / Agentic RCA MCP Agent — autonomous investigation NRAI — NL to NRQL (passive)
Bring your own LLM Any model (Claude, Gemini, Ollama) Proprietary model only
AI audit trail Full tool-call transparency Partial transparency
RAG / Doc knowledge AI Savvy Bot — native Not available
Data retention Unlimited (your storage) 30 days standard
Vendor lock-in Zero — OTel / CNCF High — proprietary NRDB
SLO management Native + visual error budgets Built-in SLOs
ML anomaly detection Rule-based via Prometheus Applied Intelligence ML
On-prem / air-gapped Fully supported Not available
Service auto-discovery Auto via Prometheus labels Auto via NR agents
Pricing

The real cost of New Relic

Pricing models that penalise growth vs infrastructure-only costs that scale cleanly.

Data ingest (GB/month) + user seats
GB-based ingestion pricing still penalises teams with high-cardinality data
Full Platform user seats are expensive — many engineers end up as Basic users with limited access
Pay-as-you-go pricing increases at least quarterly according to verified reviews
Only 30 days of data retention on standard plans — older incidents hard to investigate
Proprietary NRDB makes data extraction and migration difficult
Infrastructure cost only
Zero ingestion or host-based fees
Store 100% of logs & traces — no sampling
Predictable budget — scales with compute, not data
50–70% lower total observability spend
Open-source backends — no vendor leverage on pricing
Real Reviews

What users of competing tools actually say

Verified reviews from G2, Capterra, Gartner Peer Insights & TrustRadius.

G2 · VerifiedSRE, FinTech (10,000+ employees)

Pricing quickly escalates due to high data ingestion volume and expensive full-stack user licenses, creating budget unpredictability. Small changes in usage lead to higher bills than expected.

Budget Unpredictability
G2 · VerifiedPlatform Lead, Mid-Market SaaS

Strong vendor lock-in — all telemetry is stored in proprietary NRDB, making data extraction difficult. The NRQL query language adds another steep learning curve on top of configuration complexity.

Vendor Lock-in
Capterra · VerifiedProduct Manager, IT Services

The pay-as-you-go pricing continues to increase on at least a quarterly basis. We can only see 30 days of historical data, which hinders investigation of incidents older than a month.

Limited History
G2 · VerifiedVP Engineering, B2B Software

APM agents introduce noticeable CPU and memory overhead. The platform's AI is still essentially passive — it shows you issues but doesn't draw conclusions or run investigations automatically.

Passive AI
How REMS solves every one of these
Zero ingestion pricing — store 100% of logs and traces with no bill shock
Data never leaves your VPC — fully self-hosted, air-gappable
Active AI agent delivers root-cause conclusions, not just anomaly highlights
OTel/CNCF standards throughout — zero vendor lock-in, full data portability
AI Capability

Active AI vs passive insights

The fundamental difference between REMS and New Relic on AI is not feature depth — it's the entire paradigm.

New Relic AI
Passive anomaly detection — shows you what's wrong on a graph
LLM locked to vendor's choice — no model flexibility
Black-box ML — no audit trail on AI decisions
No RAG / knowledge base querying capability
Proprietary NRDB + NRQL — proprietary model means AI data leaves your perimeter
REMS AI
Active MCP Agent — autonomously queries metrics, traces & logs to conclude RCA
Model-agnostic — Claude, Gemini, Bedrock, or private Ollama
Full audit trail — every tool call and data source visible and explainable
Savvy Bot RAG — chat with runbooks, architecture docs alongside live telemetry
AI inference stays in your VPC — run Ollama on-prem for full air-gap compliance
The Verdict

Bottom line: should you switch?

Stay with New Relic if…

  • You're deeply integrated with NRDB and migration cost is prohibitive right now
  • Applied Intelligence anomaly detection is core to your on-call workflow
  • Your compliance posture allows SaaS telemetry and you have no data residency requirements

Switch to REMS if…

  • Quarterly price increases are straining your observability budget
  • You need historical data beyond 30 days for incident investigations
  • Data sovereignty or compliance requirements prevent sending telemetry to New Relic
  • You want AI that actively investigates — not just translates your questions to NRQL

Ready to see REMS vs New Relic live?

Get a personalised demo with your own observability stack. We'll show you the exact features that replace New Relic — and what you save.

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