Big Data BI is a BI software that can process and analyze big data. Different from traditional BI software, Big Data BI can complete real-time analysis of TB-level data. Big data can be summarized as four V's, with large data volume, high speed, various types and low value density. As the hottest word in IT industry, big data is followed by data warehouse, data security, data analysis, data mining, etc., which has gradually become the profit focus that industry people are scrambling to chase. With the advent of the era of big data, big data BI came into being.

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Open source big data ecosystem

1.HadoopHDFS, HadoopMapReduce, HBase and Hive were gradually born, and the early Hadoop ecosystem was gradually formed.

2.Hypertable is an alternative. It exists outside the Hadoop ecosystem, but it once had some users.

Integrated database/data warehouse

Ibmpuredata (netezza), oracleexadata, saphana and so on.

Shu e tou tou data warehouse

Teradata asterdata, EMC Greenplum, HPVertica and so on.

Data mart

QlikView, Tableau, Yonghong data mart and so on.

Yonghong data mart is a data storage and data processing software based on its own technology. In view of the different demand data levels, IT system architectures and storage systems that customers need to deal with, two solutions are provided for customers to choose a local mode, one is MPP mode. When the amount of data to be processed is below TB level, or a common storage structure is adopted, or a single machine can meet the performance requirements, users are advised to choose local mode. When dealing with heterogeneous database storage systems, the number of levels to be processed is above TB level and PB level, or IT systems and storage systems are distributed, or MPP mode is needed to meet the performance requirements. The parallel processing mode based on distributed architecture is more suitable for customers' needs.