A kind of memory database engine based on column-storage techniques

Big data query requests higher performance in cloud computing environment, but traditional relational DBMS can not achieve high query speed when processing large volume data, so it is a trend to apply column-storage techniques to process big data query in the field of data management. But deploying row-storage and column-storage databases simultaneously for OLTP and OLAP applications makes heavy burdens to enterprises. To enhance the query performance on big data and do not deploy column-storage databases, this paper proposed a database engine which is based on column-storage and memory techniques. It can rapidly load big data from row-storage databases and return query result in a short time. Experiments show that this engine is more efficient than the typical column-storage database MonetDB when querying big data.