Database systems were mainly used for online transaction processing in which queries for On-Line Transaction Processing (OLTP) systems that typically access only a small portion of a database, Online Analytical Processing (OLAP) queries may need to aggregate large portions of a database which often leads to performance issues. In this paper, a proposed BatchDB new memory database engine is designed and implemented in hybrid OLTP and OLAP workloads for distributed system. This method is chosen because of high level of data freshness and minimizes load interaction between the transactional and analytical engines. It facilitates real time analysis over fresh data under fixed SLAs for both OLTP and OLAP workloads and it dependent on replication, workload type (OLTP and OLAP) and a light-weight propagation of transactional updates. The experimental results are carried out on standard benchmarks of TPC-C and TPC-H, it is observed that the proposed BatchDB achieves better throughput and latency for the corresponding transactional and analytical workloads.
