What Is GeminiDB HBase API?
GeminiDB HBase API is based on GeminiDB Cassandra API. They share some cluster components, but GeminiDB HBase API introduces its own advanced features. You can use the open-source HBase Java SDK or HBase Shell to access GeminiDB HBase API. Apache HBase Driver can be directly connected using the right protocol, so you can smoothly migrate data to GeminiDB HBase instances without refactoring.
GeminiDB HBase API strictly complies with the HBase syntax and data model. Therefore, Apache HBase applications can be easily migrated to GeminiDB HBase instances. GeminiDB HBase API also provides multiple automated management and O&M functions, such as cluster scaling in minutes, automated backup, fault detection, and multi-AZ fault tolerance. GeminiDB HBase API frees you from complex O&M and parameter tuning of open-source HBase clusters.
Architecture
Database programs on each GeminiDB HBase instance node provide standard HBase functions. A shared storage pool provides file services. You only need to connect to an open port of HBase on any node to use its functions.

Highlights
GeminiDB HBase API is a cloud-native NoSQL database service compatible with open-source HBase. With robust security and reliability, GeminiDB HBase API offers ultra-high performance and addresses pain points of open-source HBase.
- Security and reliability
- A multi-layer security system, including VPCs, subnets, security groups, SSL, and fine-grained permission control, ensures database security and user privacy.
- Cross-region active-active DR is supported. You can deploy an instance across three AZs and quickly back up or restore data.
- The distributed architecture ensures fault tolerance for N-1 nodes.
- Future-proof ecosystem
- GeminiDB HBase API can directly connect to Apache HBase Driver. For details about the compatibility list, see Compatible API and Version.
- Data can be seamlessly migrated from open-source HBase and HBase-like databases. GeminiDB HBase API can interact with peripheral components.
- Enhanced capabilities
- Data recovery capabilities such as second-level flashback and Point-In-Time Recovery (PITR) ensure high data reliability.
- Data can be quickly deleted by searching for prefixes.
- Data shard failover takes just a few seconds. GeminiDB HBase API guarantees a shorter MTTR than open-source HBase.
- Superb performance
- GeminiDB HBase API provides more than twice higher performance than open-source HBase. You can check the performance white paper.
- No pain points of open-source software
- This out-of-the-box service eliminates challenges like complex parameter tuning in open-source software.
- Storage can be scaled in seconds without interrupting services.
- Compute nodes can be added in minutes. A jitter may last only a few seconds.
GeminiDB HBase API is based on GeminiDB Cassandra API.
Typical Scenarios
- Internet
GeminiDB HBase API offers superior read/write performance, high availability, dynamic scalability, and high fault tolerance. It can handle concurrent requests at low latency, ideal for Internet websites with large data volumes, for example, product catalogs, recommendations, personalized engines, and transaction records.
Advantages
Large-scale clusters
A single cluster can contain up to 100 nodes, which is ideal for Internet applications with large data volumes and write workloads.
High availability and scalability
A faulty node does not affect the entire cluster. Compute nodes and storage can be quickly added without interrupting services.
High-concurrency writes
Powerful write performance helps you handle a huge number of concurrent e-commerce transactions.
- Industrial data collection
GeminiDB HBase API is compatible with the HBase ecosystem and integrates data collected from multiple terminal sources. It imports data and stores collected metrics in real time. GeminiDB HBase API works with upstream and downstream big data components to implement aggregation analysis and real-time statistics.
Advantages:
Large-scale clusters
GeminiDB HBase API is suitable for industrial manufacturing scenarios where a large number of metrics need to be collected and stored.
High availability and performance
Data can be written to databases around the clock.
Fast backup and restoration
Storage snapshots speed up backup and recovery.
Scale-out in minutes
Nodes can be added in minutes to effortlessly handle surges in jobs and projects.
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