Cloud-native databases have become the de-facto choice for mission-critical applications on the cloud due to the need for high availability, resource elasticity, and cost efficiency. Meanwhile, driven by the increasing connectivity between data generation and analysis, users prefer a single database to efficiently process both OLTP and OLAP workloads, which enhances data freshness and reduces the complexity of data synchronization and the overall business cost. In this paper, we summarize five crucial design goals for a cloud-native HTAP database based on our experience and customers' feedback, i.e., transparency, competitive OLAP performance, minimal perturbation on OLTP workloads, high data freshness, and excellent resource elasticity. As our solution to realize these goals, we present PolarDB-IMCI, a cloud-native HTAP database system designed and deployed at Alibaba Cloud. Our evaluation results show that PolarDB-IMCI is able to handle HTAP efficiently on both experimental and production workloads; notably, it speeds up analytical queries up to $\times149$ on TPC-H (100 $GB$). PolarDB-IMCI introduces low visibility delay and little performance perturbation on OLTP workloads (< 5%), and resource elasticity can be achieved by scaling out in tens of seconds.

翻译：云原生数据库因其对高可用性、资源弹性及成本效率的需求，已成为云上关键业务应用的事实标准。与此同时，随着数据生成与分析之间连接性的日益增强，用户倾向于使用单一数据库高效处理OLTP与OLAP两种工作负载，这既能提升数据新鲜度，又能降低数据同步复杂度及整体业务成本。本文基于我们的经验及客户反馈，总结出云原生HTAP数据库的五个关键设计目标：透明性、具有竞争力的OLAP性能、对OLTP工作负载的最小干扰、高数据新鲜度以及卓越的资源弹性。作为实现这些目标的解决方案，我们提出了PolarDB-IMCI——一个在阿里云上设计与部署的云原生HTAP数据库系统。评估结果表明，PolarDB-IMCI能够高效处理实验与生产环境中的HTAP工作负载；尤其值得注意的是，在TPC-H（100 GB）基准测试中，其分析查询加速比可高达$\times149$。PolarDB-IMCI具有低可见延迟，且对OLTP工作负载的性能干扰极小（<5%），资源弹性可在数十秒内通过横向扩展实现。