Data value in real business environments
From real-time lakehouse analytics to the enterprise AI data platform, see how organizations across industries modernize data architecture and business analysis with MirrorShip.
中原银行：基于 StarRocks 构建 OLAP 全场景架构，统一离线与实时分析
中原银行基于 StarRocks 升级数据分析架构，分阶段完成固定报表迁移、知秋客户行为分析系统改造与实时数仓建设，统一离线与实时数据分析。改造后，固定报表查询效率提升至原来的 2.7 倍，留存分析查询效率提升超过 10 倍，存款入账核对时间由平均半小时缩短至 5 秒，为客户洞察、经营管理与实时决策提供数据支撑。
Read customer story →杭银消费金融：从 GreenPlum 到镜舟数据库 MirrorShip，构建 GLH 湖仓一体平台
杭银消费金融基于镜舟数据库 MirrorShip 构建 GLH 湖仓一体平台，替代原有 GreenPlum 数仓架构，围绕数据回溯、变更明细留存、时点一致性及跨系统日切等问题，统一数据采集、加工与分发流程。平台已接入 3,800 多张表，实现分钟级数据同步，每日支持运行 6,500 多个任务，并开放实时查询接口，为风控、经营分析、对账和监管报送提供数据支撑。
Read customer story →京东物流：基于 StarRocks 构建 Udata，实现数据服务与分析一体化
京东物流基于 StarRocks 构建 Udata 数据服务分析一体化平台，通过统一查询引擎打通多源数据，结合低代码指标配置、聚合下推和实时更新能力，解决数据孤岛、查询慢、服务重复开发及维护困难等问题。指标开发时间由一两天缩短至 30 分钟，支持将分析结果快速发布为数据服务，形成分析与服务闭环。
Read customer story →Let Business Users Access Enterprise Data in Natural Language
Built an explainable, traceable data Q&A experience on real-time data, enterprise semantics, and governance boundaries.
Elastic Analytics and Resource Isolation Under Peak Traffic
Used online scaling and workload isolation to keep core queries stable in a multi-tenant environment.
Getting Store and Product Data into Business Decisions Faster
Connected multi-source operations data and supported store, inventory, and sales analytics with unified definitions.
Data Architecture Upgrade at a Major Power Grid Enterprise
Built a high-performance, highly reliable lakehouse architecture on top of existing systems, balancing domestic innovation requirements with business continuity.
From T+1 to Seconds: A Unified Analytics Foundation for a Financial Enterprise
A high-concurrency, low-latency unified analytics foundation gives research, risk, and business teams a consistent data experience.
Cloud-Native Evolution: Upgrading an Automotive Company’s OLAP Engine Architecture
A unified real-time analytics engine replaces a multi-engine pipeline, supporting continuous growth in data scale and analytical demand.
从一个真实业务问题开始，验证 MIP 的价值
带上一个指标、流程或数据难题，和我们一起评估 MIP 如何在真实业务环境中提供支持。