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AnalyticDB:[Notice] Serverless mode released for AnalyticDB for PostgreSQL

Last Updated:Dec 22, 2023

AnalyticDB for PostgreSQL in Serverless mode was commercially released on May 18, 2022. AnalyticDB for PostgreSQL in Serverless mode supports elastic scaling within seconds and decouples computing and storage resources to reduce data storage costs.

Overview

AnalyticDB for PostgreSQL in Serverless mode provides features such as decoupling of computing and storage resources, elastic scaling within seconds, and real-time data sharing across instances. These features are implemented based on the resource pooling and massive storage capabilities that are provided by cloud infrastructures, and massively parallel processing (MPP), integrated batch processing and real-time analysis, and Serverless technologies.

AnalyticDB for PostgreSQL in Serverless mode provides the following advantages over AnalyticDB for PostgreSQL in elastic storage mode:

  • Reduces storage costs and enables on-demand resource use. You can use AnalyticDB for PostgreSQL in Serverless mode to implement cost-effective data analysis without the need to migrate your data to other storage media. This mode meets the data analysis requirements of the finance and Internet industries.

  • Optimizes high-throughput writes and high-performance batch processing operations with elastic scaling to suit the scenarios in which large amounts of data and large traffic fluctuations are involved.

Release date

May 18, 2022

Applicable scope

Important

On the international site (alibabacloud.com), AnalyticDB for PostgreSQL instances in Serverless mode can be created only on a pay-as-you-go basis.

Not all regions and zones support AnalyticDB for PostgreSQL instances in Serverless mode. If purchase is unavailable in the current region or zone, select another region or zone. Actual regions and zones that support AnalyticDB for PostgreSQL instances in Serverless mode on the buy page shall prevail.

Billing

Fees of AnalyticDB for PostgreSQL in Serverless mode consist of compute node fees and disk storage fees.

References