←Story detail

Trending story

Alibaba Cloud OSS launches the new version of MetaQuery

1 reports1 story updatesUpdated Oct 21 08:27

Understand this story

AI overview

Alibaba Cloud OSS launches the new version of MetaQuery. According to an article published by the Alibaba Cloud Developer Community AI on October 21, 2026, Alibaba Cloud OSS has launched a "object bucket + vector bucket + table bucket" three-bucket-in-one architecture, unifying unstructured data, vector data, and structured data onto the same storage foundation. The article states that a single file in an object bucket supports up to 48.8TB, with 12 nines of data reliability; the vector bucket supports trillion-scale vector volumes and millisecond-level similarity retrieval; the table bucket natively integrates Apache Iceberg, and concurrent write TPS for 500 tables can reach more than 10 times that of self-built Iceberg solutions. The article also breaks down the four-layer cloud-native architecture and hands-on steps such as bucket creation, SDK uploads, and batch operations and maintenance with ossutil. There are currently no subsequent development facts.

AI-generated from public reports

Latest development · Report

A Comprehensive Analysis of Alibaba Cloud OSS Object Storage: Unifying Object Buckets, Vector Buckets, and Table Buckets

Developments

1 confirmed developments

  1. Alibaba Cloud OSS launches new version of MetaQuery

    Source:English text is being prepared.

Reports and discussion timeline

Browse reports and discussion by time. Their evidence levels remain distinct.

Oct 21

  1. Alibaba Cloud Developer Community AI

    A Comprehensive Analysis of Alibaba Cloud OSS Object Storage: Unifying Object Buckets, Vector Buckets, and Table Buckets

    Alibaba Cloud OSS has launched a unified "object bucket + vector bucket + table bucket" architecture that consolidates unstructured data, vector data, and structured data onto a single storage foundation. Object buckets support a maximum single file size of 48.8TB and data reliability of 12 nines; vector buckets support trillion-scale vector volumes and millisecond-level similarity search; table buckets natively integrate Apache Iceberg, and concurrent write TPS across 500 tables can reach more than 10 times that of self-built Iceberg solutions. The article also breaks down the four-layer cloud-native architecture and hands-on steps such as creating a Bucket, uploading via SDK, and batch operations with ossutil.

Related stories

  1. Related storiesDatabricks releases long-term memory system MemCurrent
  2. Related storiesEnglish translation is being prepared.
  3. Related storiesEnglish translation is being prepared.
  4. Related storiesDatabricks AI Search adds support for three types of table sources