FusionInsight Intelligent
Data Lake

Architecture

HUAWEI CLOUD FusionInsight Intelligent Data Lake enables full-lifecycle data management, covering collection, storage, computing, management, and usage. It supports the deployment of up to 20,000 nodes in a cluster, while rolling upgrades help prevent service interruptions. And, with more than 1000 refined and visualized Operations and Maintenance (O&M) metrics, cluster management is made more reliable, secure, fault-tolerant, and easy to use.

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• MRS

  MRS can build logical, real-time, and offline data lakes with one architecture to provide cloud-native big data solutions for both governments and enterprises. Featuring a range of components such as Spark, ClickHouse, HetuEngine, Hive, HBase, and Hudi, diverse scenarios are supported, including real-time or offline analysis, interactive query, real-time retrieval, multimode analysis, data warehouse, data access, and data governance.

  DWS

  DWS is a distributed data warehouse with analysis and hybrid load capabilities. It can handle petabytes of data, performing multimode analysis and real-time processing for a data warehouse or data mart. DWS provides real-time analysis and decision-making for hybrid load scenarios, and has been widely adopted for core analysis systems in finance, government, and telecom sectors.

  DGC

  A one-stop full-lifecycle data development and operation platform, DGC provides functions such as data integration, development, governance, service, and visualization. It also supports intelligent construction of industry knowledge libraries, and incorporates data foundations such as big data storage, computing, and analytics engines, helping enterprises quickly build out their data operations.

  GES

  Offering hyper-scale integrated graph query and analysis, GES provides more than 30 high-performance algorithms for diverse scenarios and supports the query of tens of billions of vertices and hundreds of billions of edges in just seconds. It's especially well suited for scenarios involving large volumes of relationship data, including social applications, enterprise relationship analysis, risk control, personalized recommendations, and anti-fraud applications.