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Feature/Aspect | GreptimeDB | Apache Druid |
---|---|---|
Data Model | Unified Observability Database | Real-time OLAP Analytics Database |
Value Model | Multi-Value (supports complex data structures) | Multi-Value (dimensions and metrics) |
Multi-model Support | Metrics, Logs & Traces in one database | Primarily event/fact data for analytics |
Query Languages | SQL & PromQL (dual interface) | SQL & Native JSON API |
Ingestion Protocols | SQL gRPC InfluxDB Line Protocol Prometheus Remote Storage OpenTelemetry HTTP API | Kafka Kinesis Pulsar HTTP Batch files |
Data Retention | Flexible TTL policies with tiered storage | Segment-based retention with automated expiration |
Continuous Aggregation | Built-in SQL aggregation, Pipeline ETL engine & Flow streaming computation | Roll-ups and pre-aggregation at ingestion time |
Use Cases | Unified observability, real-time analytics, IoT monitoring, edge computing | Business intelligence, user-facing analytics, interactive dashboards |
Architecture | Cloud-native distributed with compute-storage separation | Microservices architecture (Broker, Historical, Middle Manager) |
Storage Format | Apache Parquet (columnar, compressed) | Time-partitioned segments in datasources |
Storage Scalability | Object storage integration with unlimited capacity | Deep storage with automatic tier management |
High Availability | Native clustering with automatic failover | Deep storage with coordinator-based failover |
License | Apache 2.0 | Apache 2.0 |
Deployment Options | Single-node, cluster, Kubernetes-native, edge-to-cloud with unified API | Multi-component deployment (brokers, historicals, coordinators) |
Operational Complexity | Single unified system with simplified Kubernetes operations | Complex multi-service orchestration |
Written Language | Rust (memory safety, SIMD optimizations) | Java (ecosystem compatibility, no native SIMD) |