Content Lake-海外

Challenges in Massive Data Processing and Analysis

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

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