Overview
Challenges
Architecture
Benefits

Solution Overview

As customers' businesses grow and their data volume keeps increasing, there are more and more business systems and business logic becomes more and more complicated. At this time, sharding is a must for a conventional online database. However, the sharded architecture cannot meet the needs of correlation statistics and real-time analysis. Then, the products of real-time data warehouse came into being. Due to the complexity and high cost of real-time data warehouse, not all enterprises need to build a whole set of ecological links. OceanBase's HTAP model was born for this purpose. By using one set of engine, it supports high concurrent online throughput and provides real-time online analysis capabilities for massive data, empowering enterprises to improve their working efficiency and innovate continuously.

Business Challenges

Poor real-time performance

Offline data warehouses often only provide T+1 data capability. Moreover, the separate construction of real-time data warehouse is relatively complicated for small and medium-sized enterprises, and requires additional human power costs to maintain the data synchronization link.

Poor resource isolation

If resource isolation in an HTAP architecture cannot be guaranteed, once the database that undertakes key transactions is affected by analytical and batch-type business, it often directly leads to a drop in online transactions and serious damage to business.

Limited capability

Limited capability: Due to the synchronization latency, it is impossible to guarantee real-time data consistency In traditional primary/standy cluster in case of large transactions or DDL operations. SQL optimizer of conventional databases cannot support complex analysis of multiple tables across shards.

Solution Architecture

  • OceanBase Database's HTAP mode makes it possible for direct business analytics query without waiting for T+1 data, enabling real-time marketing analytics directly in the online library.

Benefits

Strong Data Update Capability

Relational database-based data update capability with very low latency between replicas.

Multi-model Support

Support HBase and Table model APIs, and supports semi-structured data formats such as JSON.

HTAP Capability

Provide a reliable TP/AP resource isolation solution with the resource group isolation technology.

Distributed Parallel Computing Engine

The Powerful SQL optimizer supports parallel computing and analysis of massive data.

Flexible Scalability

A single cluster can have a maximum of 1,500 nodes, with data capacity reaching petabyte level.