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About Grafana Mimir
Grafana Mimir is a scalable, high-performance time-series database designed specifically for large-scale monitoring and observability use cases. Developed by Grafana Labs and built on top of the proven Cortex project, Mimir is optimized for handling Prometheus metrics at massive scale with multi-tenancy support. It provides long-term storage for Prometheus metrics and includes advanced features like query acceleration and horizontal scaling. Click here to read the full performance comparison report between GreptimeDB and Grafana Mimir.
GreptimeDB vs. Grafana Mimir
Feature/AspectGreptimeDBGrafana Mimir
Data ModelUnified Observability DatabaseTime-Series Database (Prometheus-focused)
Value ModelMulti-Value (supports complex data structures)Single-Value (metrics only)
Multi-model SupportMetrics, Logs & Traces in one databaseMetrics only (requires Loki for logs, Tempo for traces)
Ingestion ProtocolsSQL
gRPC
InfluxDB Line Protocol
Prometheus Remote Storage
OpenTelemetry
HTTP API
Prometheus Remote Write
InfluxDB Line Protocol
OpenTelemetry
Grafana Agent
Query LanguagesSQL & PromQL (dual interface)PromQL only
Data RetentionFlexible TTL policies with automatic tieringConfigurable retention with compaction
Continuous AggregationBuilt-in SQL aggregation, Pipeline ETL engine & Flow streaming computationRecording rules and alerting rules
Use CasesUnified observability, real-time analytics, IoT monitoring, edge computingLarge-scale Prometheus monitoring, multi-tenant environments
ArchitectureCloud-native distributed with compute-storage separationMicroservices architecture with horizontal scaling and object storage
Storage FormatApache Parquet (columnar, compressed)Prometheus TSDB blocks with object storage
Multi-tenancyBuilt-in tenant isolation and resource managementAdvanced multi-tenancy with query isolation
PerformanceSub-second query response with advanced indexingOptimized for high-cardinality Prometheus workloads
LicenseApache 2.0AGPLv3 (with commercial offering)
Deployment ComplexitySingle system deploymentComplex microservices deployment (ingester, distributor, querier, etc.)
Operational ModelSelf-managed or fully managed cloudPrimarily cloud-managed (Grafana Cloud)
Written LanguageRust (memory safety, performance)Go (ecosystem compatibility)

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