One-click copy tells your AI Agent how to install and use GreptimeDB.

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GreptimeDB: One Database for Metrics, Logs & Traces

Source: https://greptime.com/product/db

Unified Observability Engine

Metrics, logs, traces, and wide events in one database.OpenTelemetry-nativeingestion,SQL + PromQLquery, Flow engine for continuous aggregation and metric derivation. One system replaces Prometheus + Loki + Elasticsearch.

Object Storage First — Up to 50x Cost Reduction

Compute-storage disaggregationarchitecturewith object storage (S3, Azure Blob, GCS) as primary. Scale storage and compute independently. Pay for what you use — no over-provisioning.

Drop-In Compatibility

PromQL-compatible for existing Prometheus dashboards and alerts. Loki Push API and Elasticsearch bulk API for log ingestion. Jaeger Query API for trace visualization. Grafana datasource, MySQL/PostgreSQL wire protocol. Migrate without rewriting.

High-Performance Columnar Engine

Built with Rust on Apache Arrow and DataFusion.Rich indexing(inverted, fulltext, skipping) enables sub-second queries on petabyte-scale datasets. Handles high-dimensional, high-cardinality observability events.

Stateless Scale-Out

Designed forKubernetes. Stateless compute nodes scale horizontally — add nodes to scale, remove without data loss. No Thanos-style sidecar complexity.

Edge to Cloud

Deploy on ARM-basededgedevices or cloud clusters with identical APIs. Bandwidth-efficient sync between edge and cloud. One binary, from a Raspberry Pi to a 100-node cluster.

How does GreptimeDB compare to InfluxDB, TimescaleDB, ClickHouse, Loki, and Elasticsearch?In published benchmarks, GreptimeDB writes about 2× faster than InfluxDB and 2.17× faster than TimescaleDB, with time-range queries up to 67× faster and storage as low as 1/18 the size on the same dataset. For logs, ingestion runs 1.5× faster than Loki and queries 40 to 500× faster; storage lands around 50% of ClickHouse and 12.7% of Elasticsearch. Methodology and full numbers are in thebenchmark reportsandcompare pages.

Can I store metrics, logs, and traces in one database?Yes. GreptimeDB takes data through OpenTelemetry OTLP, Prometheus Remote Write, Loki Push, Elasticsearch Bulk, and Jaeger Query APIs, and stores all three signals in the same columnar engine. You query everything with SQL or PromQL, so a single query can join metrics and logs without ETL. The data model is wide events. For details, readWhy GreptimeDBand theIntegrations Overview.

Is the open-source version a stripped-down edition?No. The open-source build ships the full distributed system: cluster deployment, object storage, the Flow engine for continuous aggregation, and every ingestion and query protocol. Enterprise adds operational and scaling features (5× bulk ingestion, auto repartition, read replicas, LDAP/RBAC, the management console, 24/7 support), but the core engine and APIs are the same. See thefeature comparison.

What deployment options are supported?GreptimeDB runs as a single-binary standalone (Linux, macOS, ARM edge devices, Raspberry Pi) or as a Kubernetes cluster with stateless compute and storage on object stores. The same binary handles a Raspberry Pi or a 100-node cluster, and edge nodes sync to cloud clusters over the same APIs. For production storage use S3, GCS, or Azure Blob; for cluster metadata use etcd, MySQL, or PostgreSQL. Setup steps are in theinstallation guide.

Which protocols, SDKs, and tools work out of the box?- Ingestion: OpenTelemetry OTLP, Prometheus Remote Write, InfluxDB Line Protocol, Loki Push, Elasticsearch Bulk, MySQL, PostgreSQL, gRPC.

• Query: SQL, PromQL, Jaeger Query API.
• SDKs: Go, Java, Rust, Erlang, .NET, TypeScript, plus any OpenTelemetry SDK or MySQL/PostgreSQL driver.
• Grafana: official plugin, Prometheus data source, or MySQL data source.

Per-protocol setup:Ingest Data.

Who’s running GreptimeDB in production?Li Auto runs GreptimeDB on-vehicle across its EV production fleet to capture raw telemetry at the edge and save tens of millions in cloud bandwidth costs (case study). OceanBase Cloud runs 80+ GreptimeDB clusters carrying 300TB+ of logs and SQL audit data, with storage cost down by over 60% after migrating off Grafana Loki (case study). Other industries with public deployments: e-commerce observability, AI infrastructure, industrial IoT. More inUse Cases.

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