The new distributed graph architecture promises unified transactional and analytical processing, enabling enterprises to ...

OLTP systems provide means to highly efficient execution of a large number of small transactions and reliable access to data stored in the result of the transactions.

While OLTP databases sometimes also support analytical queries, that functionality is often performed in separate OLAP (online analytical processing) databases or data warehouses.

The 2.0 version of Splice Machine's relational database brings together the scalability of Hadoop and the in-memory performance of Spark.

This results in dramatically faster large-scale analytics and transactions without significantly increasing development and management overhead. To learn more about accelerating MySQL for Demanding ...

There’s no denying that analytic (i.e. OLAP) and transactional (i.e. OLTP) workloads put different demands on the underlying database. They have different I/O patterns, different latency expectations, ...

The startup, SnappyData, has developed an in-memory hybrid transactional analytics database that brings together OLTP, OLAP and Apache Spark to ease the pain of customers that until now have had ...

Simba Technologies Inc., a provider of standards-based data access products, solutions and services for both relational and multi-dimensional data sources, has announced that Oracle's Technology ...