Abstract Window queries are important analytical tools for ordered data and have been researched both in streaming and stored data environments. By incorporating ideas for window queries from existing streaming and stored data systems, we propose a new window syntax that makes a wide range of window queries easier to write and optimize. We have implemented this new window syntax in SQL++, an SQL extension that supports querying semistructured data, on top of AsterixDB, a Big Data Management System, thus allowing us to process window queries over large datasets in a parallel and efficient manner.

Couchbase Server is a highly scalable document-oriented database management system. With a shared-nothing architecture, it exposes a fast key-value store with a managed cache for sub-millisecond data operations, indexing for fast queries, and a powerful query engine for executing declarative SQL-like queries. Its Query Service debuted several years ago and supports high volumes of low-latency queries and updates for JSON documents. Its recently introduced Analytics Service complements the Query Service. Couchbase Analytics, the focus of this paper, supports complex analytical queries (e.g., ad hoc joins and aggregations) over large collections of JSON documents. This paper describes the Analytics Service from the outside in, including its user model, its SQL++ based query language, and its MPP-based storage and query processing architecture. It also briefly touches on the relationship of Couchbase Analytics to Apache AsterixDB, the open source Big Data management system at the core of Couchbase Analytics.

The BEA aqualogic data services platform (ALDSP) is a middleware platform for creating services that integrate and manipulate information from disparate enterprise data sources. This paper provides a technical overview of the all-new update support in ALDSP 3.0, released in January 2008. It describes the update side of data services, our unique model for making update automation transparent and flexible, and the use of the XQuery Scripting Extension (XQSE) for further customizing the system's default handling of updates. It also gives an overview of the ALDSP update processing machinery, including the automatic generation of update maps from read functions, translation of update maps into update virtual machine (UVM) programs, the UVM instruction interpreter, and SQL generation for updates to data drawn from relational data sources.

The AquaLogic Data Services Platform (ALDSP) is a middleware platform for building data services that integrate and provide operations over data drawn from spanning multiple heterogeneous information sources. A data service consists of an XML Schema instance, describing its information content, and a collection of XQuery functions and procedures that comprise its set of operations. This paper describes access control in ALDSP. We describe ALDSP's securable resource hierarchy, its fine-grained access control capabilities for securing portions of data service schemas, how XQuery can be used to specify data-driven security policies, and how user identity mapping is supported. We then provide an in-depth overview of how ALDSP works, including implementation techniques to keep access control checking from interacting badly with view rewriting, query optimization, and caching.

The AquaLogic Data Services Platform (ALDSP) is a BEA middleware platform for creating services that access and manipulate information drawn from multiple heterogeneous sources of data. The integration logic for read services is specified declaratively using the XQuery language. ALDSP 3.0, available in December 2007, includes a new XQuery-based Scripting Extension - XQSE - that enables developers to write procedural as well as declarative logic without leaving the XQuery world. In this paper, we describe the XQSE extensions to XQuery and show how they help to support important new classes of data services in ALDSP 3.0.

We showcase the BEA AquaLogic Data Services Platform (ALDSP), a middleware infrastructure product that enables the declarative development of data services for service-oriented architectures (SOA). ALDSP includes support for modeling networks of interrelated data services, for realizing data services using either graphical or source-based XQuery editors, for testing data services as they are developed, and for identifying and incorporating changes in the structure of the underlying sources of data. Physical data sources supported include relational tables and views, Web services, packaged applications, stored procedures, XML files, delimited files, and custom Java applications. Data service definitions can be layered; as with relational views, such layering is virtual, and is rewritten away at query compilation time. ALDSP supports both read and update data service functions, and the ALDSP XML query runtime includes a number of interesting query operators and distributed query optimizations. In addition, ALDSP supports function caching, fine-grained security, and SQL-based data access as well as providing service-based and XQuery access to SOA data. We plan to demonstrate as much of this as time permits.