Neusoft Select Data Warehouse
Neusoft Select Data Warehous (Neusoft Select ) is a distributed database applicable to cloud-native environments, developed by Neusoft’s expert team based on the MPP architecture and the open source platform of Pivotal Greenplum, and enjoying independent intellectual property rights. This database enables your company to manage, control, and concurrently process massive data, thus providing a solid and reliable data foundation for the flexible scaling of your IT architecture.
Meanwhile, Neusoft Select supports various application scenarios like private and public clouds to minimize the management and operation costs of your company.
Adopt the shared-nothing /MPP architecture; support the linear scaling for storage and query/load by row/column as well as Scatter/Gather parallel data flow technology; display relatively high performance in customer management, BI, ODS, data warehouse, data mart and other projects.
Enable the multilevel fault tolerance and redundancy which ensure the continuous automatic operation and data integrity in case of the software and hardware failures of the data warehouse system.
Support SQL standards, client access and third-party tools; enable the uniform data distribution to all nodes and the automatic parallel processing by the system. Involve no complicated tuning due to extremely few DBA workloads .
Provide the strong interactive Web-based performance monitoring tool that supports SNMP protocols, real-time/historical view queries , and email notification.
Boost excellent dynamic scale-out capabilities based on the X86 architecture and the Greenplum database. Rely on scaling nodes to linearly increase the capacity and processing performance of clusters, thus meeting your needs at different business development stages and realizing the low-cost scaling.
Unified Analytic Processing
Provide a unified platform for data warehouses, markets, ELT, text mining, and statistical operations. Enable the parallel data analysis at all levels in SQL, MapReduce, R and other languages.
- Support the SQL standard and the standard database interfaces (SQL, ODBC, JDBC, DBI)
- Support schemas (star, snow, 3NF, hybrid)
- Support indexes (B-Tree, Bitmap, etc.)
- Support high-performance loading for parallel big data;
- Meet the needs for complicated queries of massive data through the rich scalability and language support.