CHALLENGER
TDengine
AGPL licensed · IoT-focused design · no native observability protocols
GREPTIMEDB
GreptimeDB
Apache 2.0 licensed, observability-native with PromQL + SQL
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TDengine comparison at a glance.
See what changes operationally at scale.
TDengine is a time-series database designed for IoT and industrial data. Licensed under AGPL v3, which may impose source-disclosure obligations for network-accessible deployments. Features a "Super Table" concept for IoT device templates, but lacks native observability protocol support (no PromQL, no OpenTelemetry, no log or trace ingestion).
Feature comparison
| Feature/Aspect | GreptimeDB | TDengine |
|---|---|---|
| Data Model | Metrics, Logs & Traces in one database | Industrial IoT Time-Series Database |
| Value Model | Multi-Value (supports complex data structures) | Multi-Value with Super Table templates |
| Multi-model Support | Metrics, Logs & Traces in one database | Time-series data with IoT-specific optimizations |
| Ingestion Protocols | SQL gRPC InfluxDB Line Protocol Prometheus Remote Storage OpenTelemetry Loki Push API Elasticsearch Bulk API HTTP API | RESTful API SQL INSERT MQTT (Enterprise/Cloud) OPC-UA (Enterprise/Cloud) Industrial protocols |
| Query Languages | SQL & PromQL (dual interface) | Standard SQL with time-series functions |
| Data Retention | Flexible TTL policies with tiered storage | Configurable retention with automatic deletion |
| Continuous Aggregation | Built-in SQL aggregation, Pipeline ETL engine & Flow streaming computation | Stream processing with caching and data subscription |
| Use Cases | Unified observability, real-time analytics, IoT monitoring, edge computing | Industrial IoT, smart manufacturing, connected vehicles, energy monitoring |
| Architecture | Cloud-native distributed with compute-storage disaggregation | Distributed design with Super Table templates |
| Storage Format | Apache Parquet (columnar, compressed) | Native time-series optimized storage |
| Storage Scalability | Object storage integration with unlimited capacity | Distributed storage with automatic sharding |
| High Availability | Native clustering with automatic failover | Multi-replica deployment with data synchronization |
| License | Apache 2.0 | AGPL v3.0 (core), Commercial (enterprise) |
| Deployment Options | Single-node, cluster, Kubernetes-native, edge-to-cloud with unified API | On-premise, cloud, hybrid deployment with Kubernetes |
| Operational Complexity | Single unified system with simplified Kubernetes operations | Requires understanding of Super Table concepts |
| Written Language | Rust (memory safety, performance) | C (system-level performance) |
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