About GreptimeDB
GreptimeDB is an
open-source, high-performance time-series database designed to unify metrics, logs, and traces in a single engine. It's built to replace the traditional three-system observability stack (Prometheus + Loki + Elasticsearch) with one integrated solution.
Key Capabilities
Unified data processing: GreptimeDB handles metrics, logs, and traces natively through a consistent data model, eliminating data silos and the need to context-switch between systems.
Dual query languages: Query with both </user-guide/query-data/sql/|SQL> and </user-guide/query-data/promql/|PromQL>, giving you real-time monitoring capabilities plus deep analytics in one system.
Protocol compatibility: Drop-in compatible with Prometheus, Jaeger, Loki, MySQL, PostgreSQL, and Elasticsearch — migrate without rewriting queries or pipelines.
Cost efficiency: Leverages cloud object storage (S3, Azure Blob, GCS) as the primary data backend with compute-storage separation. Teams have achieved
up to 50x storage cost reduction compared to traditional solutions.
Architecture Highlights
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Compute-storage separation: Compute nodes scale independently; data persists in object storage with local disk serving as cache
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Kubernetes-native: Built for cloud-native deployments with true elastic scaling
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Written in Rust: High performance with columnar storage, advanced compression, and vectorized query execution
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Flexible deployment: Supports everything from edge devices to cloud clusters with consistent APIs
Real-World Performance
GreptimeDB recently achieved
#1 performance in JSONBench for handling 1 billion JSON documents, outperforming ClickHouse and other competitors. The database also includes a built-in </user-guide/flow-computation/overview/|streaming engine> for real-time aggregations and analytics.
Getting Started
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Try instantly:
GreptimeCloud — fully-managed DBaaS, no deployment needed
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Self-hosted:
GreptimeDB on GitHub
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Community: Join
Slack or explore
GitHub Discussions
📖 Source:
GreptimeDB Documentation and
Why GreptimeDB