Compare log platforms, wide-event systems, error monitoring, data infrastructure, and SQL event analytics using one production workflow.
Reviewed by the Telemetry product team on . We checked the comparison sources, test criteria, workload assumptions, and which tools to keep when migrating. Who reviews this page
Test the tools on work you actually do
Before testing tools, decide what data to collect and exclude, who will query it, and how they will respond to problems. Specify retention and expected volume.
Evaluation criteria
Does the team need purpose-built application events, unrestricted logs, metrics, traces, errors, infrastructure monitoring, or security analysis?
Telemetry is not a substitute for every specialist signal, and broad observability suites should not be evaluated only as event tables.
Will operators use SQL, a vendor query language, search, notebooks, prebuilt views, or several interfaces?
Have the people who respond to incidents write and check queries in each tool.
Are services sending completion events, free-form logs, spans, metrics, or documents whose fields change?
Collection flexibility affects schema ownership, cardinality, privacy review, and the meaning of every aggregate.
Who owns clusters, indexes, agents, collectors, retention tiers, upgrades, and query performance?
Managed convenience and infrastructure control have different costs and responsibilities.
Is cost driven by hosts, users, ingest volume, retained bytes, indexed fields, query runtime, custom metrics, or add-ons?
Entry prices are not comparable until the same workload and retention assumptions are modeled.
Can a chart lead to the exact rows, query, trace, error, or infrastructure signal needed to verify an incident?
During an incident, responders need to check the rows or traces behind a chart.
Start from the job
Goal
Full-stack infrastructure, metrics, traces, and logs
Evaluate first
Datadog, New Relic, Elastic, Splunk, or Grafana
Why
Start with broad suites when the buying decision includes host and service telemetry beyond application outcome events.
Goal
High-volume logs or wide-event investigation
Evaluate first
Axiom, Better Stack, Honeycomb, Loki, or ClickHouse
Why
Test the native ingestion, query, retention, and operational model on the expected volume and cardinality.
Goal
Error-centric debugging and release context
Evaluate first
Sentry and the existing application stack
Why
Keep stack traces, grouping, release health, and issue workflows in an error specialist when responders depend on them.
Goal
Bounded structured events with DataFusion SQL
Evaluate first
Telemetry
Why
Use event tables when you need SQL joins across product usage, reliability, AI runs, billing, and customer results.
Telemetry analyzes structured events. Keep your existing tools where you still need their logs, traces, metrics, evaluations, error diagnostics, or infrastructure monitoring.
Reproducible test
Sourced deep dives
Datadog covers observability and security across your infrastructure. Telemetry hosts structured application events, SQL dashboards, and threshold alerts for teams that need to query their own workflows.
Read comparisonClickHouse is a columnar analytics database, and ClickStack adds observability tools. Telemetry hosts event ingestion, SQL queries, dashboards, and alerts so you do not have to assemble or operate that stack.
Read comparisonAxiom offers event ingestion, search, APL queries, dashboards, and monitors. Telemetry uses typed application event tables and SQL. Its coding-agent prompts help you add instrumentation and build queries from your codebase.
Read comparisonBetter Stack combines logs, dashboards, alerting, incident management, and uptime monitoring. Telemetry focuses on application event tables and SQL queries, with prompts that help a coding agent add instrumentation to your codebase.
Read comparisonHoneycomb supports high-cardinality debugging with wide events and distributed traces. Telemetry stores application and business events in SQL tables, with dashboards and threshold alerts.
Read comparisonGrafana Cloud and Loki combine logs, metrics, traces, dashboards, and alerts. Telemetry hosts JSON event tables and SQL for teams that need to analyze application workflows.
Read comparisonSentry combines error monitoring, tracing, profiling, session replay, and logs around application health. Telemetry is the narrower alternative when a team's first requirement is custom structured workflow events and SQL analysis rather than exception-centric debugging.
Read comparisonSplunk offers search, security analytics, logs, infrastructure monitoring, APM, real-user monitoring, and OpenTelemetry collection. Telemetry focuses on application events that you choose to send and query with SQL.
Read comparisonElastic Observability combines Elasticsearch, Kibana, logs, metrics, APM, profiling, and OpenTelemetry collection. Telemetry is the focused alternative when the main job is managed application-event ingestion and SQL analysis without operating or modeling a broader Elastic deployment.
Read comparisonNew Relic is a broad observability platform spanning APM, infrastructure, logs, browser, mobile, synthetics, errors, and NRQL. Telemetry is the narrower choice when a team wants custom structured outcomes, SQL, and a lightweight event-analysis workflow.
Read comparisonMixpanel is a product and digital analytics platform built around behavioral reports such as insights, funnels, flows, retention, and cohorts. Telemetry is the narrower choice for SQL over application-owned product and operational events.
Read comparisonAmplitude is a digital analytics platform with product-analysis workflows for events, funnels, retention, journeys, cohorts, and experimentation. Telemetry focuses on compact structured events and explicit SQL.
Read comparisonUse the free plan and synthetic fixtures to compare ingestion, SQL, dashboards, exports, and alerts before moving production data.