Last reviewed . Product packaging and pricing can change; verify the linked vendor sources before buying.
Try LangSmith alongside Telemetry
Choose one LangSmith workflow and test both systems with the same fixed dataset. Check which capabilities you still need before changing production monitoring.
- 1
Inventory LangSmith
LangSmith traces, runs, model interactions, and tool calls
- 2
Map one workflow
No direct equivalent; retain LangSmith for detailed run trees and send approved terminal events with a safe correlation identifier.
- 3
Dual-run the fixture
Exercise one successful run, tool failure, recovered retry, and terminal failure while checking the trace-to-outcome handoff.
- 4
Record the decision
List every required trace, dataset, evaluator, annotation, experiment, prompt, and deployment workflow before comparing products.
How Telemetry is different
- LangSmith follows LLM application runs as traces; Telemetry stores selected application outcomes as named event tables.
- LangSmith includes evaluator, dataset, annotation, and experiment workflows that have no built-in Telemetry equivalent.
- Telemetry applies the same SQL event model to agent outcomes, application reliability, billing, jobs, webhooks, and product behavior.
When Telemetry is a good fit
- The team needs aggregate agent reliability, cost, quality, and outcome analysis more than trace replay or prompt inspection.
- You want to query results without collecting prompts, completions, retrieved content, or tool payloads.
- LangSmith can remain the trace and evaluation system while Telemetry receives selected versioned outcomes.
Where each product is strongest
LangSmith
- Detailed tracing of model, tool, chain, and agent execution with run-level inspection and feedback.
- Datasets, offline and online evaluation, human review, experiments, and testing workflows for LLM applications.
- A stronger fit when teams need an integrated LLM development and evaluation lifecycle or supported self-hosted deployment options.
Telemetry
- A small set of allowlisted run, request, tool, evaluation, and outcome events that remain directly queryable with SQL.
- Cross-workflow analysis that can connect an agent result with release, customer tier, product action, billing, or later business outcome.
- Dashboards and threshold alerts that use saved SQL queries and defined event fields.
Evaluation checklist
Test the decision with a real workflow
- 1List every required trace, dataset, evaluator, annotation, experiment, prompt, and deployment workflow before comparing products.
- 2Run one frozen evaluation and one production investigation, then compare evidence detail, privacy, SQL flexibility, integration work, and handoffs.
- 3Verify current cloud and self-hosted packaging, retention, seats, evaluation usage, support, and operational requirements with the vendor.
Migration path
Plan the query and event migration before changing tools
List the queries, alerts, exports, and retention you use today. Define the event fields they need and translate one query. Run both systems with the same test data. Check null handling, timestamps, and aggregates before moving more queries.
LangSmith workflow
LangSmith traces, runs, model interactions, and tool calls
Telemetry mapping
No direct equivalent; retain LangSmith for detailed run trees and send approved terminal events with a safe correlation identifier.
Dual-run validation
Exercise one successful run, tool failure, recovered retry, and terminal failure while checking the trace-to-outcome handoff.
LangSmith workflow
LangSmith datasets, evaluators, annotations, and experiments
Telemetry mapping
Selected ai_output_reviewed events record evaluator, rubric, dataset, prompt, and release versions. Telemetry does not run evaluations or curate datasets.
Dual-run validation
Compare a frozen candidate and baseline with identical examples, evaluator configuration, thresholds, and coverage rules.
LangSmith workflow
LangSmith aggregate monitoring and feedback views
Telemetry mapping
Reviewed SQL queries, dashboards, and alerts across run, cost, evaluation, customer, and product-outcome events.
Dual-run validation
Dual-run the same aggregate questions and verify event grain, joins, denominators, time windows, and missing evaluations.
Try one workflow
Start with one backend workflow
Pick an API route, AI workflow, webhook, or job queue. Send structured events and query them before expanding coverage.
Category buying guide
Compare AI observability tools for your workflow
Compare AI observability approaches for traces, prompts, evaluations, model cost, tool reliability, SQL analysis, and product outcomes.
Read the comparison guideMore comparisons
PostHog for backend events
PostHog combines product analytics, funnels, retention, SQL, and a data warehouse. Telemetry focuses on backend event tables and SQL dashboards. A coding agent can add the instrumentation from your codebase.
Read comparisonDatadog alternative for startups
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 logging API without running ClickHouse
ClickHouse 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 alternative for structured event analytics
Axiom 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 Logs alternative for SQL event analytics
Better 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 alternative for lightweight wide events
Honeycomb 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 Loki alternative for structured log SQL
Grafana 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 alternative for structured events and SQL
Sentry 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 alternative for structured events
Splunk 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 alternative for structured event SQL
Elastic 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 alternative for structured events
New 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 comparisonTelemetry vs Langfuse for AI observability
Langfuse provides LLM traces, prompt management, evaluations, datasets, and experiments. Telemetry stores events for agent runs and product activity so you can query their cost, reliability, and results with SQL.
Read comparisonTelemetry vs Arize Phoenix
Arize Phoenix is an open-source AI observability and evaluation platform built around traces, prompts, datasets, and experiments. Telemetry focuses on compact structured outcomes and SQL.
Read comparisonTelemetry vs Pydantic Logfire
Pydantic Logfire combines OpenTelemetry-based application monitoring with AI tracing and conversation views. Telemetry stores selected application outcomes in tables you can query with SQL.
Read comparisonTelemetry vs Mixpanel
Mixpanel 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 comparisonTelemetry vs Amplitude
Amplitude 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 comparisonTelemetry vs Braintrust
Braintrust is an AI evaluation and observability platform built around experiments, datasets, scorers, prompts, and production traces. Telemetry focuses on SQL over selected AI and product outcomes.
Read comparisonTelemetry vs Helicone
Helicone combines an AI gateway with LLM request observability, sessions, cost analytics, caching, and alerts. Telemetry is a provider-neutral SQL layer for selected AI and application outcomes.
Read comparisonTelemetry vs Opik
Opik is an open-source LLM evaluation and observability platform with traces, datasets, metrics, experiments, and test suites. Telemetry uses SQL to analyze selected AI and application results.
Read comparisonTelemetry vs W&B Weave
W&B Weave is an AI observability and evaluation platform with traces, datasets, scorers, versioning, feedback, and production monitoring. Telemetry focuses on SQL over selected AI and product outcomes.
Read comparisonTelemetry vs MLflow for GenAI
MLflow provides OpenTelemetry-compatible GenAI tracing, evaluations, prompt versioning, experiments, and production monitoring. Telemetry stores selected task results in event tables that you can join with other application data using SQL.
Read comparisonTelemetry vs OpenLIT
OpenLIT is an open-source, OpenTelemetry-native AI engineering platform with auto-instrumentation, traces, evaluations, prompts, experiments, dashboards, and collectors. Telemetry focuses on SQL outcome events.
Read comparison