AnyShare Family 7_Cooperation cases -AISHU

Challenges in Massive Data
Processing and Analysis

Challenge 1:
Difficult to store massive data

•High requirements for reliability and scalability

•Diverse content data

•Backup performance bottleneck of massive un-structured data

Challenge 2:
Difficult to use massive data

•The diversification and rapid growth of unstruc-tured data make retrieval difficult

•Massive data analysis and mining are difficult

Challenge 3:
Difficult to support large-scale access

•Data aggregation brings access pressure

•Diverse access needs to ensure access experi-ence

AnyShare Family 7 Content Lake
Storage and Processing of Massive Unstructured Data

Unified Content Management

Aggregate document data, metadata and index to realize manageable, retrievable and reusable content management

Easy Scalability

Adopt scale-out cluster architecture to store object, metadata and index. Support OBS of multi-cloud environment to eliminate single-node bottleneck

Processing Capability for Massive Data

Support EB level of unstructured data and metadata processing, with a reliability of up to 99.999%

More Powerful Solutions, More Intelligent Experience

Explore More Application Scenarios of Content Lake

Scenario 2: Build a smart traffic content lake

•AnyShare can store large amounts of violation images and automatically recognize plate number and car color from them to support further inquire and management in business system.

•AnyShare can be integrated into the mobile police system for enforcement officers to upload and download files.

Cornerstone for Storage and Processing of
Massive Unstructured Data