JSON vs. Oracle Big Data SQL Cloud Service vs. Python vs. QML Comparison Chart

Oracle Big Data SQL Cloud Service enables organizations to immediately analyze data across Apache Hadoop, NoSQL and Oracle Database leveraging their existing SQL skills, security policies and applications with extreme performance. From simplifying data science efforts to unlocking data lakes, Big Data SQL makes the benefits of Big Data available to the largest group of end users possible. Big Data SQL gives users a single location to catalog and secure data in Hadoop and NoSQL systems, Oracle Database. Seamless metadata integration and queries which join data from Oracle Database with data from Hadoop and NoSQL databases. Utilities and conversion routines support automatic mappings from metadata stored in HCatalog (or the Hive Metastore) to Oracle Tables. Enhanced access parameters give administrators the flexibility to control column mapping and data access behavior. Multiple cluster support enables one Oracle Database to query multiple Hadoop clusters and/or NoSQL systems.

QML is a declarative language that allows user interfaces to be described in terms of their visual components and how they interact and relate with one another. It is a highly readable language that was designed to enable components to be interconnected in a dynamic manner, and it allows components to be easily reused and customized within a user interface. Using the QtQuick module, designers and developers can easily build fluid animated user interfaces in QML, and have the option of connecting these user interfaces to any back-end C++ libraries. QML is a user interface specification and programming language. It allows developers and designers alike to create highly performant, fluidly animated and visually appealing applications. QML offers a highly readable, declarative, JSON-like syntax with support for imperative JavaScript expressions combined with dynamic property bindings.