CHALLENGER
Grafana Tempo
Traces only · requires Prometheus + Loki for full observability · TraceQL
GREPTIMEDB
GreptimeDB
Metrics, Logs & Traces in one database · SQL + PromQL · single deployment
Skip to content 
Traces solved. Metrics and logs?
Still two more systems to run.
Grafana Tempo is a distributed tracing backend developed by Grafana Labs, designed to store and query trace data at scale without requiring sampling. It uses object storage (S3, GCS, Azure) for cost-effective long-term retention and supports Jaeger, Zipkin, and OpenTelemetry protocols. Tempo is designed to work alongside Prometheus (metrics) and Loki (logs) — meaning a full observability stack requires operating three separate systems.
Feature comparison
| Feature/Aspect | GreptimeDB | Grafana Tempo |
|---|---|---|
| Data Model | Metrics, Logs & Traces in one database | Distributed Tracing Backend |
| Value Model | Multi-Value (supports complex data structures) | Trace spans with attributes |
| Multi-model Support | Metrics, Logs & Traces in one database | Traces only (requires separate systems for metrics/logs) |
| Query Languages | SQL & PromQL (dual interface) | TraceQL |
| Ingestion Protocols | SQL gRPC InfluxDB Line Protocol Prometheus Remote Storage OpenTelemetry Loki Push API Elasticsearch Bulk API HTTP API | Jaeger Zipkin OpenTelemetry OTLP |
| Data Retention | Flexible TTL policies with tiered storage | Object storage-based retention with compaction |
| Continuous Aggregation | Built-in SQL aggregation, Pipeline ETL engine & Flow streaming computation | Service maps and span metrics generation |
| Deployment Complexity | Single system deployment | Multi-component deployment (Distributor, Ingester, Querier, Compactor) |
| Use Cases | Unified observability, real-time analytics, IoT monitoring, edge computing | Distributed tracing, request flow analysis, latency troubleshooting |
| Architecture | Cloud-native distributed with compute-storage disaggregation | Microservices architecture with object storage backend |
| Storage Format | Apache Parquet (columnar, compressed) | Parquet files in object storage |
| Storage Scalability | Object storage integration with unlimited capacity | Native object storage design for unlimited scale |
| High Availability | Native clustering with automatic failover | Stateless components with object storage persistence |
| License | Apache 2.0 | Apache 2.0 |
| Written Language | Rust (memory safety, performance) | Go (ecosystem compatibility) |
| Deployment Options | Single-node, cluster, Kubernetes-native, edge-to-cloud with unified API | Microservices mode, scalable mode with object storage |
| Operational Complexity | Single unified system with simplified Kubernetes operations | Requires coordination with Prometheus and Loki for full observability |
All Comparisons
Side-by-side feature breakdowns for additional alternatives.
Stay in the loop
Join our community
Get the latest updates and discuss with other users.