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Join us at two must-attend conferences this summer and claim your exclusive SWAG! ๐ŸŽ

IOT TECH EXPO, June 5-6 in Santa Clara! Booth 270 | DATA + AI SUMMIT, June 11-13 in San Francisco! Booth e12

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GreptimeDB

Integrate faster and focus on your data
Compatibility
Compatible with MySQL, PostgreSQL, OpenTSDB, InfluxDB, Prometheus and many more.
Seamless Integration
Easily integrate with your backend with Java & Go SDKs, or using our HTTP APIs.
Performance
Written in Rust, sustainable and safe, high performance with ultra-low storage cost.
Extendable
Scale each module easily and independently with the decoupled, cloud-native architecture.
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GreptimeCloud

Your Prometheus has a Cloud.
Out-of-the-box Experience
Be up and running in seconds. No configuration required. Query console, dashboards and database interfaces are all built-in and instantly available.
Broad Integrations
Native Prometheus compatibility. Works well with most tools you are already familiar with, from your favorite programming language to various tools.
Serverlessly Scalable
Focus on your data and allocate capacity based on your ingestion rate and queries, instead of CPU/memory resources.
Simplified Operations
Fully managed cloud hosting, including continuous upgrades and expanding deployments, TLS-encrypted protocols, the option to bring your own cloud and manymore.
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Cloud Observability

Compatible with open standards, enhanced Prometheus with superior query engine and long-term storage.

Start ingestion from various data sources, Prometheus Remote Write, Vector and OpenTelemetry

Native PromQL and SQL as query languages

Built-in visualization and alerting with a few clicks, Grafana compatible

Rules and configurations are managed by Git and compatible with Prometheus

Built for kubernetes stack, AI applications and more

Connected-Car/IoT

Bring your Connected-Car/IoT data stack to cloud era, fast, scalable and cost-efficient

Small footprint database for edge in-device storage and computation

Managed end-to-end data ingestion from edge to cloud, improved collaboration of cloud and edge

Use SQL optimized for time-series data to dramatically improve data analysis efficiency

Fully separation of storage and compute, scale independently for max efficiency

Store and access historical data from bottomless storage

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