  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.
