AI visibility report
AI visibility report for Axiom in Observability & Monitoring.
Outside the top three on 24 of the 25 prompts buyers actually ask.
New Relic is cited on 11 of those losses.
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Track Axiom across these prompts daily.
Start free trialStill absent from 99.3% of tracked prompt responses
Top-3 citations across 150 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Grok
Google AI Mode
Gemini Search
Bing Copilot
ChatGPT
PerplexityHow to read this. Axiom appears in 0.7% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.
Where Axiom is losing
Prompts where competitors are visible and Axiom is not.
These prompt-level losses are the first prompts to track and repair.
Where Axiom is winning
No clear strengths identified yet.
Where Axiom is losing5
Which SaaS monitoring platforms have the lowest ingestion lag during high-volume log bursts so alerting stays fast?
Competitors on 4 platforms
Track this promptWhich observability platforms integrate with deployment pipelines to correlate performance regressions with specific code changes?
Competitors on 4 platforms
Track this promptWhich observability platforms support real user monitoring alongside backend APM for correlating frontend and backend performance?
Competitors on 4 platforms
Track this promptWhich APM tools integrate best with cloud provider managed databases and serverless functions for end-to-end visibility?
Competitors on 3 platforms
Track this promptWhat observability platforms can a small engineering team realistically get to meaningful dashboards and alerting on quickly?
Competitors on 3 platforms
Track this prompt
Track Axiom daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Axiom is a cloud-native event data platform built for unified observability and AI engineering at petabyte scale. Founded in 2017 and headquartered in San Francisco, it serves 40,000+ organizations—from developer startups to enterprises—with a dual-datastore architecture: EventDB for schema-less log, trace, and event ingestion, and MetricsDB for high-cardinality time-series data. Axiom's serverless design eliminates sampling constraints and infrastructure management, compressing data up to 95% to dramatically reduce storage costs versus legacy alternatives. The platform unifies logs, traces, and metrics in a single console, queryable via the Axiom Processing Language. A dedicated AI engineering toolkit traces multi-step LLM agent workflows, evaluates prompts, and tracks cost and token usage. Usage-based pricing starts at $25/month, with a generous always-free tier and automatic volume discounts.
Axiom is an agent-native observability and event data platform that unifies logs, distributed traces, metrics, and AI engineering telemetry in a single serverless data store, designed to capture 100% of event data at petabyte scale without sampling—dramatically reducing observability costs compared to legacy tools.
Key Facts
- Founded
- 2017
- HQ
- San Francisco, CA, USA
- Founders
- Neil Jagdish Patel, Seif Lotfy, Gord Allott
- Employees
- 11-50
- Funding
- ~$41.4M
- Customers
- 40,000+ organizations
- Status
- Private
Target users
Key Capabilities10
- Petabyte-scale event ingestion with schema-less, zero-sampling architecture
- EventDB: purpose-built event/log/trace datastore with 25–50x compression and serverless querying
- MetricsDB: high-cardinality time-series datastore with no cardinality penalties (GA March 2026)
- Distributed tracing with OpenTelemetry and span waterfall visualization
- Axiom Processing Language (APL) for flexible, piped event querying
- AI engineering toolkit: multi-step agent workflow tracing, prompt evaluation, LLM cost/token/latency tracking
- MCP server for AI agent access to real-time observability data
- Usage-based pricing with automatic volume discounts and always-free tier
- Edge architecture with regional data residency (US and EU)
- Threshold and anomaly-driven alerting with real-time dashboard monitoring
Key Use Cases7
- High-volume log management and long-term retention without sampling
- Distributed tracing for microservices and serverless architectures
- AI/LLM engineering observability: tracing agent workflows, tracking prompt cost and latency
- Infrastructure and application performance monitoring
- Event-driven application development on Axiom's API/SDK layer
- Security and compliance log retention with zero blind spots
- Observability cost reduction replacing Datadog, Splunk, or CloudWatch
Axiom customer outcomes
40% reduction in observability spend; 65% faster MTTR
Global digital services company Monks switched from a legacy observability stack to Axiom, eliminating sampling-induced security blind spots and enabling cost-neutral AI adoption for their Monks.Flow platform. Incident resolution improved significantly with unified, full-retentio
Petabyte of AWS Lambda events queryable; 4 billion messages managed; 100% log retention at lower cost than logging error
GPS asset-tracking company Hapn replaced AWS CloudWatch and a rehydration-based vendor with Axiom to retain and query 100% of events from their all-Lambda serverless architecture across eleven AWS accounts. Axiom enabled affordable full-year log retention and faster customer supp
Recent Trend
How AI describes Axiom3
| | Axiom / Better Stack | Modern, developer-first platforms designed to ingest terabytes of logs cheaply, often utilizing raw structured JSON.
I'm evaluating observability platforms — which ones are best suited for a logs-first approach versus a traces-first approach?
Axiom --------- Best for: High-volume logging on a budget. If your small team is generating massive amounts of logs (e.g., from an API, high-traffic web app, or LLM application) and you are terrified of getting a massive bill from Datadog or Logst...
What observability platforms can a small engineering team realistically get to meaningful dashboards and alerting on quickly?
Axiom --------- Axiom is built specifically to ingest massive volumes of event and log data with zero sampling, maintaining sub-second query speeds across petabytes of high-cardinality data.
Which observability platforms have the best ad-hoc query experience for high-cardinality log data during an active incident?
Most cited sources3
Alternatives in Observability & Monitoring6
Axiom positions itself as a cost-disruptive alternative to expensive legacy observability tools (Datadog, Splunk, Elastic) by offering no-sampling, petabyte-scale event data ingestion with ~95% compression, usage-based pricing, and no artificial data limits.
- Its dual-datastore architecture (EventDB for events/logs/traces, MetricsDB for high-cardinality metrics) underpins a unified observability and AI engineering platform.
- Axiom explicitly targets engineering teams priced out of full-retention logging by incumbents, and differentiates further by positioning as the observability layer for AI/LLM workflows—tracing agent pipelines, tracking cost and token usage, and evaluating prompts.
- The platform is cloud-only and self-serve, with transparent volume discounts, contrasting with negotiation-heavy enterprise sales models at Datadog and Splunk.
Reviews
Praised
- Dramatically lower cost vs. Datadog, Splunk, and CloudWatch
- No-sampling, 100% data retention at petabyte scale
- Fast time-to-value and easy onboarding
- OpenTelemetry-native integration
- APL query power and flexibility for large datasets
- 95% data compression reduces storage footprint
- Responsive team and active Discord community
- Unified logs, traces, and metrics in one interface
Criticized
- Limited pre-built dashboards; requires manual widget construction
- APL query language learning curve for non-KQL users
- Cloud-only deployment with no self-hosting option
- Fewer native APM and anomaly alerting features than Datadog or New Relic
- Smaller ecosystem of integrations vs. full-suite incumbents
- No built-in RUM, uptime monitoring, or incident management
No verified scores were found on G2 or Gartner Peer Insights for the axiom.co observability product. Developer community sentiment—from blog posts, comparison articles, and Discord discussions—is broadly positive, highlighting affordable cost relative to Datadog/Splunk/CloudWatch, seamless OpenTelemetry integration, fast time-to-value, and the power of APL for ad-hoc querying. Common criticisms include the need to build dashboards from scratch, the learning curve of APL for users unfamiliar with KQL, the absence of self-hosting options, and less comprehensive pre-built APM and alerting compared to full-suite platforms.
Pricing
Axiom Cloud uses usage-based pricing anchored to three dimensions: data loading compute (billed in credits at $0.06–$0.12/GB, decreasing with volume), query compute ($0.08–$0.20/GB-hour), and compressed storage ($0.030/GB/month). A $25/month platform fee applies. A free Personal plan includes 500 GB/month data loading, 10 GB-hours query compute, and 25 GB storage with 30-day retention—no credit card required. The Axiom Cloud paid tier includes 1,000 GB/month data loading, 100 GB-hours query compute, and 100 GB storage free before usage charges. Enterprise add-ons include SAML SSO ($100/month), Directory Sync ($100/month), RBAC ($50/month), and Audit Log ($50/month). Pre-purchasing compute credits yields up to 30% discount (1M+ credits at $0.70 each). SOC-2 and HIPAA BAA available under NDA with minimum annual spend.
Limitations
- Axiom is currently cloud-hosted only with no self-managed or BYOC deployment option (an edge architecture was launched in March 2026 for data residency, but full self-hosting is not offered).
- The proprietary APL query language, while similar to KQL, requires learning and does not offer SQL-native queries.
- The platform provides fewer pre-built dashboards than Datadog or New Relic, requiring more manual dashboard construction.
- Built-in APM RED metrics, anomaly-based alerting, and automated service maps are less mature than full-stack competitors.
- With a reported team of ~20 employees, platform breadth and enterprise support depth lag behind larger vendors.
- No RUM, synthetic monitoring, or uptime/incident management capabilities are offered natively.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Google AI Mode | Gemini Search | Bing Copilot | ChatGPT | Perplexity | Grok |
|---|---|---|---|---|---|---|
Capability0/5 cited (0%) | ||||||
Which observability platforms support business-level metrics like conversion funnels alongside infrastructure and application telemetry? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Which monitoring platforms have the best anomaly detection — automatically surfacing regressions without manual threshold tuning? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
I'm evaluating observability platforms — which ones are best suited for a logs-first approach versus a traces-first approach? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Which enterprise observability platforms handle multi-tenant environments with isolated views per team or service best? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which observability platforms support real user monitoring alongside backend APM for correlating frontend and backend performance? | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Developer Experience0/5 cited (0%) | ||||||
Which observability platforms have the best ad-hoc query experience for high-cardinality log data during an active incident? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which observability platforms have the best alert management features to help teams reduce alert fatigue through smart routing and thresholds? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which observability platforms make it easiest for developers new to OpenTelemetry to adopt a trace-first workflow? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited |
Which observability platforms make it easiest to correlate a user-reported error with the right trace and log lines in a distributed system? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which monitoring platforms offer the best on-call experience — from alert firing through to root cause identification? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited |
Integrations & Ecosystem0/5 cited (0%) | ||||||
Which APM tools integrate best with cloud provider managed databases and serverless functions for end-to-end visibility? | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Which observability backends support receiving OpenTelemetry data simultaneously to avoid vendor lock-in? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited |
Which observability platforms integrate with deployment pipelines to correlate performance regressions with specific code changes? | A competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Which observability platforms integrate best with incident management and on-call scheduling tools for a seamless response workflow? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
What log shipping tools work best for getting structured logs from containerized applications to an observability platform without code changes? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited |
Performance & Reliability1/5 cited (20%) | ||||||
What observability platforms offer the best tail-based sampling for high-throughput systems to control costs without losing important traces? | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which SaaS monitoring platforms have the lowest ingestion lag during high-volume log bursts so alerting stays fast? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Your brand and a competitor were cited |
Which observability platforms handle data retention and query performance best as log volume grows into terabytes per day? | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which cloud observability platforms have the most reliable synthetic monitoring checks with the lowest false positive rates? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which distributed tracing platforms add the least overhead to latency-sensitive APIs — safe to run in production at full sampling? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Setup & First Run0/5 cited (0%) | ||||||
What's the quickest distributed tracing platform to set up across a microservices architecture on a container orchestration platform? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited |
What are the best cloud-hosted observability platforms for migrating from a legacy self-hosted logging stack without losing historical data? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
What observability platforms support unified metrics, traces, and logs instrumentation for Node.js and Python polyglot applications? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
What observability platforms can a small engineering team realistically get to meaningful dashboards and alerting on quickly? | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Which APM tools have the best day-one onboarding to get immediate value without drowning in noise? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited |
Turn this matrix into daily prompt monitoring.
Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | New Relic | 21.3% | 19.2% | 2.0% | 19.3% | 58.0% | #14.7 | +0.44 |
| 2 | Datadog | 15.3% | 18.5% | 4.7% | 9.3% | 76.0% | #16.2 | +0.38 |
| 3 | Splunk | 12.0% | 11.7% | 0.7% | 8.7% | 37.3% | #19.7 | +0.43 |
| 4 | Grafana | 10.0% | 10.0% | 5.3% | 3.3% | 8.7% | #26.1 | +0.50 |
| 5 | Honeycomb | 8.7% | 10.3% | 2.0% | 5.3% | 38.0% | #24.3 | +0.55 |
| 6 | Dynatrace | 8.0% | 12.5% | 6.0% | 3.3% | 53.3% | #40.9 | +0.35 |
| 7 | Better Stack | 6.7% | 5.7% | 0.7% | 0.7% | 8.0% | #13.5 | +0.42 |
| 8 | Logz.io | 4.7% | 2.8% | 0.0% | 4.0% | 4.7% | #9.6 | +0.45 |
| 9 | Coralogix | 4.0% | 2.8% | 0.0% | 0.0% | 5.3% | #6.6 | +0.62 |
| 10 | Elastic | 4.0% | 3.9% | 0.7% | 1.3% | 26.7% | #28.4 | +0.53 |
| 11 | Chronosphere | 1.3% | 1.1% | 0.0% | 0.0% | 4.7% | #21.7 | +0.55 |
| 12 | Axiom | 0.7% | 1.1% | 0.0% | 0.7% | 4.0% | #74.7 | +0.80 |
| 13 | Mezmo | 0.7% | 0.4% | 0.7% | 0.0% | 0.7% | #75.0 | +0.80 |
| 14 | Sentry | 0.0% | 0.0% | 0.0% | 0.0% | 6.7% | — | — |
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