Grafana Labs Grafana Tempo

Name: Grafana Labs Grafana Tempo
Brand: Grafana Labs

Leader

Open observability cloud

Est 2014|Valuation $9.5B|Raised $907.9M

LinkedIn 299K|Website|Web traffic 1.5M|FTEs 1,600|HQ New York, NY

MarketsObservability Platform Application Performance Monitoring (APM)

01Competitive Landscape

Narrative analysis

Tempo vs Jaeger - Jaeger is widely adopted and supports multiple storage backends; it emphasizes different operational tradeoffs, including storage scaling and TTL practices. - Tempo differentiates itself by minimizing indexing overhead and relying on object storage; organizations should evaluate whether Tempo’s query model and operational requirements match their needs. Tempo vs Datadog / New Relic (APM suites) - Datadog and New Relic provide integrated platforms (APM + infrastructure + logs + additional capabilities) with a single-vendor experience for telemetry and monitoring. - Pricing and packaging differ: some APM vendors use per-host or specialized SKU pricing, while Grafana Cloud uses modular, consumption-based billing across telemetry types. Cost outcomes depend on ingestion volume and retention patterns. Tempo vs Honeycomb - Honeycomb focuses on iterative exploration and high-cardinality analysis with a productized UX. Teams that prioritize exploratory analysis and a managed experience may prefer Honeycomb over self-hosted or highly composable stacks.

Adoption trends (cautious statement)

Grafana Labs’ growth, funding, and LGTM messaging indicate notable market activity, but Tempo-specific market share and adoption metrics are not clearly reported in public sources.

	Grafana Tempo	Jaeger	Honeycomb
Starting Price	OSS: open-source license; managed via Grafana Cloud (usage-based billing)	OSS: open-source license; infrastructure costs depend on storage choice	SaaS with tiered plans and event/usage-based billing
Typical Fit	Teams seeking OSS tracing with object-storage-based economics and Grafana integration	Teams using CNCF-standard tracing with flexible storage backends and Jaeger UI	Teams prioritizing exploratory debugging and a productized analysis UX
Key Strength	Architecture that reduces indexing and leverages object storage for cost control; integration with Grafana for cross-signal workflows	Mature ecosystem and multiple storage backend options; broad adoption	Productized experience oriented toward high-cardinality analysis and rapid iteration
Key Weakness	Requires assembly of components for a full APM experience; ingestion and UX expectations can require significant configuration	Operating scalable storage and building the desired UI/UX can add complexity	Pricing can scale with event volume; less flexible for self-host-first strategies

01Competitive Landscape

Narrative analysis

Tempo vs Jaeger

Jaeger is widely adopted and supports multiple storage backends; it emphasizes different operational tradeoffs, including storage scaling and TTL practices.
Tempo differentiates itself by minimizing indexing overhead and relying on object storage; organizations should evaluate whether Tempo’s query model and operational requirements match their needs.

Tempo vs Datadog / New Relic (APM suites)

Datadog and New Relic provide integrated platforms (APM + infrastructure + logs + additional capabilities) with a single-vendor experience for telemetry and monitoring.
Pricing and packaging differ: some APM vendors use per-host or specialized SKU pricing, while Grafana Cloud uses modular, consumption-based billing across telemetry types. Cost outcomes depend on ingestion volume and retention patterns.

Tempo vs Honeycomb

Honeycomb focuses on iterative exploration and high-cardinality analysis with a productized UX. Teams that prioritize exploratory analysis and a managed experience may prefer Honeycomb over self-hosted or highly composable stacks.

Adoption trends (cautious statement)

Grafana Labs’ growth, funding, and LGTM messaging indicate notable market activity, but Tempo-specific market share and adoption metrics are not clearly reported in public sources.

	Grafana Tempo	Jaeger	Honeycomb
Starting Price	OSS: open-source license; managed via Grafana Cloud (usage-based billing)	OSS: open-source license; infrastructure costs depend on storage choice	SaaS with tiered plans and event/usage-based billing
Typical Fit	Teams seeking OSS tracing with object-storage-based economics and Grafana integration	Teams using CNCF-standard tracing with flexible storage backends and Jaeger UI	Teams prioritizing exploratory debugging and a productized analysis UX
Key Strength	Architecture that reduces indexing and leverages object storage for cost control; integration with Grafana for cross-signal workflows	Mature ecosystem and multiple storage backend options; broad adoption	Productized experience oriented toward high-cardinality analysis and rapid iteration
Key Weakness	Requires assembly of components for a full APM experience; ingestion and UX expectations can require significant configuration	Operating scalable storage and building the desired UI/UX can add complexity	Pricing can scale with event volume; less flexible for self-host-first strategies