GeminiDB Cassandra API is a cloud-native, distributed NoSQL database based on Huawei-developed architecture with decoupled storage and compute. It is compatible with the Cassandra ecosystem and supports Cassandra Query Language (CQL), which gives you SQL-like syntax. This high availability database is secure and scalable, can be deployed, backed up, or restored quickly, and supports functions like monitoring and alarm reporting. You can also expand storage or compute resources separately.

Open Source Compatibility

Full compatibility with open-source Cassandra APIs, drivers, and development tools

Excellent Performance

It addresses long tail latency and provides capabilities such as inverted indexing and multi-dimensional query

Reliability

Strong enterprise-class data consistency, fault reconstruction, and backup and restoration

Easy Management

Fully managed instances, allowing for operations on instances on the console with just a few clicks

Comprehensive Solutions

Social Networking

Scenario Description

In social networking scenarios, GeminiDB Cassandra API is often used to store operations such as following, posting, and liking. Smooth scaling can quickly handle traffic surges of hot topics.

Advantages

High-concurrency write

High write performance makes it easy to handle a large volume of data. The storage engine based on the LSM tree is a great fit for write-intensive scenarios.

Scaling in minutes

Scaling operations can be completed in minutes, so you can respond quickly to sudden traffic bursts.

IoT

Scenario Description

GeminiDB Cassandra API can support highly concurrent writes of massive data generated by IoT devices, including data for meteorology, smart city monitoring, and wearable devices.

Advantages

High performance

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.

High data reliability

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

Large capacity

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

Data Warehouse

Scenario Description

GeminiDB Cassandra API can serve as a service database or a data analytics platform. It can analyze massive advertising data, historical orders, feeds, messages, logs, and recommendations to form new user and behavior profiles.

Advantages

Storage for massive data and high performance

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.

High availability and easy maintenance

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.

Documentation

Getting Started

Getting Started

Buying and connecting to an Instance

API Reference

Connection Methods

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Advanced Level

Advanced Level

Data Backup

Monitoring Metrics

Slow Query Logs

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FAQs

FAQs

What Should I Pay Attention to When Using GeminiDB Cassandra API?

Different Billing Modes

How Can I Select an AZ?

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