With a cloud-native distributed architecture and a storage engine based on the LSM tree, GeminiDB can process highly concurrent writes of massive data. The design of partitioning and sorting keys makes it easy to query IoT data of the TIME type, giving you high query performance and low latency.

There are three data copies, ensuring data security and integrity.

Petabytes of data can be stored. Storage scaling can complete within seconds and is transparent to applications.

A cloud-native architecture can store massive data, allowing you to scale out compute and storage resources separately. Ultra-high write performance enables you to quickly create data warehouses on demand.

Multi-AZ deployment provides high availability, so a cluster can still work once one of its nodes becomes faulty. Visual monitoring and alarm reporting help you keep always aware of your workload status, making O&M easy.