Both RDBMS and NoSQL database vendors have added varying degrees of support for storing and processing JSON data. Some vendors store JSON directly as text while others add new JSON type systems backed by binary encoding formats. The latter option is increasingly popular as it enables richer type systems and efficient query processing. In this paper, we present our new native JSON datatype and how it is fully integrated with the Oracle Database ecosystem to transform Oracle Database into a mature platform for serving both SQL and NoSQL style access paradigms. We show how our uniquely designed Oracle Binary JSON format (OSON) is able to speed up both OLAP and OLTP workloads over JSON documents.

Oracle release 12cR1 supports JSON data management that enables users to store, index and query JSON data along with relational data. The integration of the JSON data model into the RDBMS allows a new paradigm of data management where data is storable, indexable and queryable without upfront schema definition. We call this new paradigm Flexible Schema Data Management (FSDM). In this paper, we present enhancements to Oracle's JSON data management in the upcoming 12cR2 release. We present JSON DataGuide, an auto-computed dynamic soft schema for JSON collections that closes the functional gap between the fixed-schema SQL world and the schema-less NoSQL world. We present a self-contained query friendly binary format for encoding JSON (OSON) to close the query performance gap between schema-encoded relational data and schema free JSON textual data. The addition of these new features makes the Oracle RDBMS well suited to both fixedschema SQL and flexible-schema NoSQL use cases, and allows users to freely mix the two paradigms in a single data management system.

There has been more than decade of efforts of supporting storage, query and update XML documents in RDBMS. XML enabled RDBMS supports SQL/XML standard that defines XMLType as a SQL data type and allows XQuery/XPath embedded in XMLQuery(), XMLExists() and XMLTABLE() in SQL. In XML enabled RDBMS, both relational data and XML documents can be managed in one system and queried using SQL/XML language. However, the use case of management of document centric XML is not well-addressed due to the lacking of full text query constructs in XQuery. Recently, XQuery Full Text (XQFT) becomes the W3C recommendation. In this paper, we show how XQFT can be supported efficiently in SQL/XML for full text search of XML documents managed by XML enabled RDBMS, such as Oracle XMLDB. We present architecture of a new XML Full Text Index, XQuery compile time and run time enhancements to efficiently support XQFT in SQL/XML. We present our design rationale on how to exploit Information Retrieval (IR) techniques for XQFT support in RDBMS. The new XML Full Text Index can index common XML physical storage forms: such as text XML, binary XML, relational decomposition of the XML. Although our work is built within Oracle XMLDB, all of the presented principles and techniques in this paper are valuable enough to RDBMS industry that needs to effectively and efficiently support of XQFT over persisted XML documents.

XQuery Update Facility (XQUF), which provides a declarative way of updating XML, has become recommendation by W3C. The SQL/XML standard, on the other hand, defines XMLType as a column data type in RDBMS environment and defines the standard SQL/XML operator, such as XML Query() to embed XQuery to query XMLType column in RDBMS. Based on this SQL/XML standard, XML enabled RDBMS becomes industrial strength platforms to host XML applications in a standard compliance way by providing XML store and query capability. However, updating XML capability support remains to be proprietary in RDBMS until XQUF becomes the recommendation. XQUF is agnostic of how XML is stored so that propagation of actual update to any persistent XML store is beyond the scope of XQUF. In this paper, we show how XQUF can be incorporated into XML Query() to effectively update XML stored in XMLType column in the environment of XML enabled RDBMS, such as Oracle XMLDB. We present various compile time and run time optimisation techniques to show how XQUF can be efficiently implemented to declaratively update XML stored in RDBMS. We present how our approaches of optimising XQUF for common physical XML storage models: native binary XML storage model and relational decomposition of XML storage model. Although our study is done using Oracle XMLDB, all of the presented optimisation techniques are generic to XML stores that need to support update of persistent XML store and not specific to Oracle XMLDB implementation.

There has been a lot of research and industrial effort on building XQuery engines with different kinds of XML storage and index models. However, most of these efforts focus on building either an efficient XQuery engine with one kind of XML storage, index, view model in mind or a general XQuery engine without any consideration of the underlying XML storage, index and view model. We need an underlying framework to build an XQuery engine that can work with and provide optimization for different XML storage, index and view models. Besides XQuery, RDBMSs also support SQL/XML, a standard language that integrates XML and relational processing. There are industrial efforts for building hybrid XQuery and SQL/XML engines that support both languages so that users can manage and query both relational and XML data on one platform. However, we need a theoretical framework to optimize both SQL/XML and XQuery languages in one RDBMS. In this paper, we show our industrial work of building a combined XQuery and SQL/XML engine that is able to work and provide optimization for different kinds of XML storage and index models in Oracle XMLDB. This work is based onXML extended relational algebraas the underlying tuple-based logical algebra and incorporates tree and automata based physical algebra into the logical tuple-based algebra so as to provide optimization for different physical XML formulations. This results inlogical and physical rewritetechniques to optimize XQuery and SQL/XML over a variety of physical XML storage, index and view models, including schema aware object relational XML storage with relational indexes, binary XML storage with schema agnostic path-value-order key XMLIndex, SQL/XML view over relational data and relational view over XML. Furthermore, we show the approach of leveragingcost based XML physical rewritestrategy to evaluate different physical rewrite plans.

Efficiently storing and querying XML has been widely studied in research and industrial settings. Major RDBMS vendors now support XML as a native datatype in their systems and provide physical means of storing schema agnostic XML data. Typically this data is stored in CLOBs, BLOBs, or tree forms, with path or value indices used to efficiently process XQuery and SQL queries. However, in many use case queries derived from industrial XML applications, we find that it is very common to query XML based on a group of related property data and to query on the master-detail relationships using the SQL XMLTable construct. We propose an indexing mechanism called the XMLTable Index which is more efficient than the path and value index approach for this class of queries, and provides a way to efficiently process these queries over any physical XML storage form. The XMLTable Index complements the path/value index approach, and can be enhanced in its capabilities by using it in conjunction with path, value, text and other domain indices.