HBase Application Scenarios
Storage and Query of Message Logs
Application Scenarios:
Structured and semi-structured key-value data can be stored and queried, including messages, reports, recommendation data, risk control data, logs, and orders.
Advantages:
- Mass storage
Offline and online storage of massive volumes of key-value data, and flexible capacity expansion
- High-performance read/write
100-million-level write throughput, millisecond-level query latency for presenting online applications and reports
- Enriched ecosystem
A large number of Hadoop ecosystem components, integrated with products
Profile Storage and Query
Application Scenarios:
Labels are used to describe characteristics of people and objects. Each person or object has a set of labels that are uncertain because data is frequently updated. This type of data is widely used in marketing decision-making, recommendation, and advertising systems.
Advantages
- Sparse matrix
The sparse matrix model of HBase is suitable for storing unstructured data. No schema needs to be predefined for tables and no strict column definition is required among rows.
- Easy update
You can update any rows at any time without performance loss. HBase built-in versioning mechanism is used to save multiple historical versions of data.
Storage and Queries of Mass Key-Value Data
- Data types
Structured and semi-structured key-value data, including messages, reports, recommendation data, risk control data, logs, and orders.
- Application scenarios
CloudTable allows high-speed write of mass online and offline key-value data and low-latency data queries. It applies to online applications or report display. CloudTable can easily scaled to achieve HA and low-latency storage and queries of vast amounts of data.
- Storage and Query of Message Logs
- Profile Storage and Query
- Storage and Queries of Mass Key-Value Data