Features
ㆍSupport distributed massive parallel processing based on GPU-accelerated computation
ㆍAnalyze all areas of complex and massive data at high speed through the combination of CPU and GPU
ㆍThere is no limit to the processing capacity, and it is possible to analyze even petabyte-level large-capacity data
ㆍReduce data collection and query execution time
ㆍSignificantly faster performance than CPU-based solutions
ㆍSupport standard SQL and various programming languages, APIs, and data sources
Functions
ㆍMPP (Massively Parallel Processing)
ㅤ: Distributed parallel processing architecture using multiple GPU cards
ㅤㅤProcess the SQL query in milliseconds and return the result
ㆍDistributed Architecture
ㅤ: Distribute data across multiple GPUs, each processing data independently
ㅤㅤOutput results are merged into CPU, providing faster data loading speed
ㅤㅤAccelerate big data processing by implementing Multi Node and Multi GPU
ㆍMaster Node ? Data Node
ㅤ: Efficient use of resources with distributed architecture load balancing consisting of a master node and multiple data nodes
ㆍOpen Architecture
ㅤ: Easy integration with various devices and platforms
ㅤㅤGoogle gRPC, JDBC, ODBC / Major programming languages and APIs / Supports various data sources / BI visualization tools
ㆍStandard SQL
ㅤ: Compatible with ANSI-92 SQL / Excellent query performance
ㅤㅤUsers can develop products using their existing SQL knowledge
ㅤㅤSupport complex aggregate operations and federated queries
