Last reviewed . Product packaging and pricing can change; verify the linked vendor sources before buying.
Try W&B Weave alongside Telemetry
Choose one W&B Weave workflow and test both systems with the same fixed dataset. Check which capabilities you still need before changing production monitoring.
- 1
Inventory W&B Weave
W&B Weave traces, ops, calls, and production monitoring
- 2
Map one workflow
Compact run, model, tool, evaluation, and terminal-outcome events with a safe correlation identifier; no trace-tree equivalent.
- 3
Dual-run the fixture
Exercise one successful run, tool retry, terminal failure, and feedback event while comparing privacy boundaries and correlation.
- 4
Record the decision
List required traces, prompt or model versions, datasets, scorers, feedback, guardrails, and production-monitoring workflows.
How Telemetry is different
- Weave follows detailed LLM and agent executions as traces and versioned AI objects; Telemetry stores selected outcomes in named event tables.
- Weave includes evaluation datasets, scorers, comparisons, feedback, and AI-specific monitoring that have no built-in Telemetry equivalent.
- Telemetry applies the same SQL model to agent outcomes, product actions, billing, APIs, jobs, webhooks, and releases.
When Telemetry is a good fit
- The primary question is aggregate AI reliability, cost, adoption, or accepted outcomes rather than trace-level debugging.
- Keep detailed evaluation records in a specialist system. Send selected outcomes and their version identifiers to Telemetry.
- The team wants explicit SQL and a shared event model across AI and non-AI product workflows.
Where each product is strongest
W&B Weave
- End-to-end LLM and agent tracing with inputs, outputs, model usage, latency, cost, tool steps, and trace-level inspection.
- Datasets, evaluation pipelines, custom and built-in scorers, version tracking, feedback, and result comparison.
- A stronger fit when the team needs a connected AI development, evaluation, and production-monitoring workflow.
Telemetry
- Compact run, request, tool, evaluation, and product-outcome events queried directly with DataFusion SQL.
- Join AI results with accounts, releases, billing, reliability, and return visits.
- Your application chooses which fields to send. You can exclude prompts, outputs, retrieved content, and detailed traces.
Evaluation checklist
Test the decision with a real workflow
- 1List required traces, prompt or model versions, datasets, scorers, feedback, guardrails, and production-monitoring workflows.
- 2Run one production investigation and one frozen evaluation with the same success definition, privacy boundary, and release identifiers.
- 3Verify current hosted or self-managed deployment, access, retention, export, evaluation volume, and pricing before deciding.
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.
W&B Weave workflow
W&B Weave traces, ops, calls, and production monitoring
Telemetry mapping
Compact run, model, tool, evaluation, and terminal-outcome events with a safe correlation identifier; no trace-tree equivalent.
Dual-run validation
Exercise one successful run, tool retry, terminal failure, and feedback event while comparing privacy boundaries and correlation.
W&B Weave workflow
W&B Weave datasets, evaluations, scorers, and versioned objects
Telemetry mapping
Versioned evaluation-result events for aggregate SQL; retain Weave for dataset curation, scorer execution, comparisons, and detailed review.
Dual-run validation
Run the same frozen examples with identical model, prompt, scorer, threshold, and coverage definitions before comparing results.
W&B Weave workflow
W&B Weave trace metrics and evaluation analysis
Telemetry mapping
DataFusion SQL dashboards joining AI reliability, cost, reviewed quality, release, account, and downstream product outcomes.
Dual-run validation
Reconcile run count, token use, cost, latency, evaluated coverage, score distribution, and accepted outcomes over one closed interval.
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 LangSmith for AI observability
LangSmith provides tracing, evaluations, datasets, experiments, and deployment options for LLM applications. Telemetry stores the final results of AI and application tasks in event tables you can query 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 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