4D Cude Database

Highlights of the technical architecture

• Hybrid Workloads and Scalability

  It supports both OLTP (high-concurrency transactions) and OLAP (analytical queries) through distributed columnar storage, meeting the requirements of real-time performance and analytical needs.

• Innovation in Data Model

  Data is organized in a three-dimensional cube (Account, Data Class, Timestamp), which natively supports multi-tenancy, multiple data types, and time-series traceability.

• Governance and Flexibility

  Six categories of metadata are mounted in a schema-on-read manner, avoiding the rigidity of traditional ETL and adapting to dynamic compliance requirements (such as GDPR).

Core Competencies

• High - performance Search

  • Dual - index acceleration: Vector + BM25 hybrid index

  • Self - developed M - Stage parallel executor

  • P99 latency < 30ms under tens of millions of TPS

• Reliable Transaction Processing

  • Two - phase Raft consensus protocol

  • Revocable encrypted logs

  • Complete ACID guarantees and audit trails

• Cross - modal Analysis

  • Unified processing of structured/semi - structured data

  • Support for joint queries of graph relationships and time series

  • Real - time stream - batch integration processing

4D Cube vs Traditional Databases

• 4D Cube

  • Mixed Workload Support

    Seamless OLTP + OLAP

  • Scalability

    Horizontal elastic scaling (unlimited)

  • Search Response Time (P99)

    <30ms (10M+ TPS)

  • Metadata Flexibility

    6 dynamic dimensions

  • Transaction Safety

    Full ACID + Auditable

• Traditional Columnar Database

  • Mixed Workload Support

    OLAP-focused, weak transaction performance

  • Scalability

    Primarily vertical scaling, high cost

  • Search Response Time (P99)

    >100ms (1M+ TPS)

  • Metadata Flexibility

    Fixed schema, requires downtime for expansion

  • Transaction Safety

    Partial ACID, weak auditing