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Advances, Systems and Applications

Table 6 The description of the indicators of cloud-native dimension

From: A maturity model for AI-empowered cloud-native databases: from the perspective of resource management

Indicator

Description

Multi-tenant

Databases provide services for multiple tenants. And tenants share the resources of database servers. The multi-tenant enables cost reduction for the cloud service provider, which can pass on as savings to the tenants [50].

Compute and storage disaggregation

Computing and storage are decoupled from each other. The computing and storage resources are dynamically combined through the network. And the computing process is data-driven to realize on-demand driving better [31]. In this way, independent compute nodes can be flexibly scaled up, and storage nodes can be flexibly scaled-down, improving the cost performance of databases.

Cross-Az/Region

A logical database is divided into multiple shards, each of which is assigned to a node. These nodes can be placed and replicated in different data centers and regions [1].

Near-data processing

Using the processing capacity in the memory to process the data (such as the screening operation of the database) and only transmit the data processing results to the host. The method saves a lot of system resources and reduces time delay and energy consumption. It can be implemented by operator push-down [4].

Logs as the database

The CNDB only writes log files and plays back data at the storage layer to avoid I/O amplification. The method reduces network pressure on the cloud infrastructure [30].

Distributed and shared memory

Memory resources in different nodes are connected through a high-speed network. Databases can share data pages in the remote memory pool, similar to the shared storage pool in the shared storage architecture [51].