On-line transaction processing (OLTP) database management systems (DBMSs) often serve
time-varying workloads due to daily, weekly or seasonal fluctuations in demand, or because …

For decades, applications deployed on a world-wide scale have been forced to give up at
least one of (1) strict serializability (2) low latency writes (3) high transactional throughput. In …

For data-intensive applications with many concurrent users, modern distributed main
memory database management systems (DBMS) provide the necessary scale-out support …

Providing the ability to elastically use more or fewer servers on demand (scale out and scale
in) as the load varies is essential for database management systems (DBMSes) deployed on …

Recent deterministic database systems have achieved high scalability and high availability
in distributed environments given OLTP workloads. However, modern OLTP applications …

The consolidation of multiple tenants onto a single RDBMS instance turned out to be
benefical with respect to resource utilization and scalability. The consolidation implies that …

During the parallel execution of queries in Non-Uniform Memory Access (NUMA) systems,
the Operating System (OS) maps the threads (or processes) from modern database systems …

In the database area, elasticity of cloud computing has required data systems to increase
and decrease their resources on demand. However, traditional benchmark tools for data …

Many applications hosted on the cloud have sophisticated data management needs that are
best served by a SQL-based relational DBMS. It is not difficult to run a DBMS in the cloud …

A variety of systems for data analytics are available as cloud services today, including
Amazon Elastic MapReduce (EMR), Amazon Redshift, Azure's HDInsight, and several …