CHALLENGER
M3DB
Release cadence slowed significantly · complex multi-component ops (Coordinator, Aggregator, etcd) · metrics only
GREPTIMEDB
GreptimeDB
Actively maintained, simpler architecture, unified observability
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M3DB comparison at a glance.
See what changes operationally at scale.
M3DB was developed by Uber for large-scale metrics storage. Active development has slowed significantly. It features a multi-component architecture — M3 Coordinator, M3 Query, M3 Aggregator, and etcd — that is complex to operate. Metrics only; no native support for logs, traces, or OpenTelemetry.
Feature comparison
| Feature/Aspect | GreptimeDB | M3DB |
|---|---|---|
| Data Model | Metrics, Logs & Traces in one database | Distributed Time-Series Database |
| Value Model | Multi-Value (supports complex data structures) | Single-Value (Prometheus metrics) |
| Multi-model Support | Metrics, Logs & Traces in one database | Metrics only (requires separate systems for logs/traces) |
| Query Languages | SQL & PromQL (dual interface) | PromQL (100% compatibility) & M3QL |
| Ingestion Protocols | SQL gRPC InfluxDB Line Protocol Prometheus Remote Storage OpenTelemetry Loki Push API Elasticsearch Bulk API HTTP API | Prometheus Remote Write M3 Coordinator API Carbon (Graphite) |
| Data Retention | Flexible TTL policies with tiered storage | Configurable retention with automatic expiration |
| Continuous Aggregation | Built-in SQL aggregation, Pipeline ETL engine & Flow streaming computation | M3 Aggregator with stream-based downsampling |
| Deployment Complexity | Single system deployment | Multi-component deployment (coordinator, query, aggregator) |
| Use Cases | Unified observability, real-time analytics, IoT monitoring, edge computing | Large-scale Prometheus monitoring, metrics aggregation |
| Architecture | Cloud-native distributed with compute-storage disaggregation | Multi-component architecture (M3DB + M3 Coordinator + M3 Query + M3 Aggregator) |
| Storage Format | Apache Parquet (columnar, compressed) | M3TSZ compression (optimized Gorilla TSZ) |
| Storage Scalability | Object storage integration with unlimited capacity | Distributed storage with automatic sharding |
| High Availability | Native clustering with automatic failover | Multi-region deployment with quorum-based consistency |
| 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 | Multi-component deployment with etcd coordination |
| Operational Complexity | Single unified system with simplified Kubernetes operations | Complex multi-component operations |
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