We demonstrate SWITCH, a deep embedding of relational queries into Ruby and Ruby on Rails. With SWITCH, there is no syntactic or stylistic difference between Ruby programs that operate over in-memory array objects or database-resident tables, even if these programs rely on array order or nesting. SWITCH's built-in compiler and SQL code generator guarantee to emit few queries, addressing long-standing performance problems that trace back to Rails' Active Record database binding. "Looks likes Ruby, but performs like handcrafted SQL, " is the ideal that drives the research and development effort behind SWITCH.

A purely relational account of the true XQuery semantics can turn any relational database system into an XQuery processor. Compiling nested expressions of the fully compositional XQuery language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers.

We demonstrate an efficient LINQ to SQL provider and its significant impact on the runtime performance of LINQ programs that process large data volumes. This alternative provider is based on Ferry, compilation technology that lets relational database systems participate in the evaluation of first-order functional programs over nested, ordered data structures. The Ferry-based provider seamlessly hooks into the .NET LINQ framework and generates SQL code that strictly adheres to the semantics of the LINQ data model. Ferry comes with strong code size guarantees and complete support for the LINQ Standard Query Operator family, enabling a truly interactive and compelling LINQ demonstration. A variety of inspection holes may be opened to learn about the internals of the Ferry-based LINQ to SQL provider.

A purely relational account of the true XQuery semantics can turn any relational database system into an XQuery processor. Compiling nested expressions of the fully compositional XQuery language, however, yields odd algebraic plan shapes featuring scattered distributions of join operators that currently overwhelm commercial SQL query optimizers. This work rewrites such plans before submission to the relational database back-end. Once cast into the shape of join graphs, we have found off-the-shelf relational query optimizers - the B-tree indexing subsystem and join tree planner, in particular - to cope and even be autonomously capable of "reinventing" advanced processing strategies that have originally been devised specifically for the XQuery domain, e.g., XPath step reordering, axis reversal, and path stitching. Performance assessments provide evidence that relational query engines are among the most versatile and efficient XQuery processors readily available today.

We demonstrate the language Ferry and its editing, compilation, and execution environment FerryDeck. Ferry's type system and operations match those of scripting or programming languages; its compiler has been designed to emit (bundles of) compliant and efficient SQL:1999 statements. Ferry acts as glue that permits a programming style in which developers access database tables using their programming language's own syntax and idioms -- the Ferry-expressible fragments of such programs may be executed by a relational database back-end, i.e., close to the data. The demonstrator FerryDeck implements compile-and-execute-as-you-type interactivity for Ferry and offers a variety of (graphical) hooks to explore and inspect this approach to database-supported program execution.

The Pathfinder XQuery compiler has been enhanced by a new code generator that can target any SQL:1999-compliant relational database system(RDBMS). This code generator marks an important next step towards truly relational XQuery processing, a branch of database technology that aims to turn RDBMSs into highly efficient XML and XQuery processors without the need to invade the relational database kernel. Pathfinder, a retargetable front-end compiler, translates input XQuery expressions into DAG-shaped relational algebra plans. The code generator then turns these plans into sequences of either SQL:1999 statements or view definitions which jointly implement the (sometimes intricate) XQuery semantics. In a sense, this demonstration thus lets relational algebra and SQL swap their traditional roles in database query processing. The result is a code generator that (1) supports an almost complete dialect of XQuery, (2) can target any RDBMS with a SQL:1999 language interface, and (3) exhibits quite promising performance characteristics when run against high-volume XML data as well as complex XQuery expressions.