Last reviewed . Product packaging and pricing can change; verify the linked vendor sources before buying.
Try Splunk alongside Telemetry
Choose one Splunk workflow and test both systems with the same fixed dataset. Check which capabilities you still need before changing production monitoring.
- 1
Inventory Splunk
Splunk event data, fields, and source types
- 2
Map one workflow
Selected application outcomes modeled as named event tables with stable typed columns.
- 3
Dual-run the fixture
Replay a fixed test dataset. Compare accepted rows, timestamps, field types, nulls, and duplicate handling.
- 4
Record the decision
Inventory every SPL search, detector, alert, dashboard, security workflow, and non-event signal before considering a migration.
How Telemetry is different
- Telemetry starts with named JSON event tables and DataFusion SQL; Splunk supports a much broader machine-data, observability, and security ecosystem with SPL and SignalFlow workflows.
- Telemetry collects selected application, product, billing, job, webhook, and agent results. It does not provide general log ingestion or full-stack collection.
- Telemetry does not replace Splunk APM, infrastructure monitoring, real-user monitoring, security analytics, or the Splunk integration ecosystem.
When Telemetry is a good fit
- You need to query selected application events, rather than collect every source of machine data in one place.
- Engineers and analysts prefer familiar SQL for rates, joins, funnels, cohorts, and outcome analysis.
- The team already has specialist tracing, infrastructure, security, or incident systems where those remain necessary.
Where each product is strongest
Splunk
- A broad platform for logs, search, security analytics, infrastructure, APM, digital experience monitoring, dashboards, alerts, and service-level workflows.
- OpenTelemetry collection and queries that connect logs, metrics, and traces during an investigation.
- A stronger fit when an operations or security organization needs broad collection, correlation, governance, and an established ecosystem.
Telemetry
- Send JSON events for your application and business processes, then query them as SQL tables.
- Event ingestion and SQL queries for teams that already know which events and fields they need.
- Copy schemas, SQL recipes, and coding-agent prompts to add events to one workflow at a time.
Evaluation checklist
Test the decision with a real workflow
- 1Inventory every SPL search, detector, alert, dashboard, security workflow, and non-event signal before considering a migration.
- 2Replay one safe event fixture and compare field typing, timestamp behavior, query definitions, result validation, and alert transitions.
- 3Use current vendor documentation to compare ingestion, retention, users, premium capabilities, and operating ownership for the actual workload.
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.
Splunk workflow
Splunk event data, fields, and source types
Telemetry mapping
Selected application outcomes modeled as named event tables with stable typed columns.
Dual-run validation
Replay a fixed test dataset. Compare accepted rows, timestamps, field types, nulls, and duplicate handling.
Splunk workflow
SPL searches, dashboards, and alerts
Telemetry mapping
Reviewed DataFusion SQL, dashboards, and threshold alerts for the specific migrated decisions.
Dual-run validation
Dual-run counts, rates, percentiles, and alert state over the same closed UTC interval.
Splunk workflow
APM, infrastructure, RUM, security, and general log search
Telemetry mapping
No direct equivalent. Keep Splunk or another specialist to query logs, traces, metrics, security data, and other machine data together.
Dual-run validation
Map every incident and security dependency before changing collectors, retention, or access.
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 structured logging and event analytics tools
Compare log platforms, wide-event systems, error monitoring, data infrastructure, and SQL event analytics using one production workflow.
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 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 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