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Extending Informix®
Beyond standard relational database objects, HCL Informix® can be extended to handle specialized data types, access methods, routines, and other objects. Informix includes many built-in extensions that are fully integrated in the database server. Informix also provides DataBlade® modules, which are packages of extended database objects for a particular purpose and that are installed separately from the database server. Alternatively, you can create your own user-defined objects for Informix.
Creating extensions
You can create user-defined data types, routines, access methods, and other database objects to suit your needs. You can use application programming interfaces to write user-defined routines and applications that access data in Informix® databases.
R-Tree Index User's Guide
The Informix® R-Tree Index User's Guide describes the HCL Informix R-tree secondary access method and how to access and use its components.
Develop DataBlade® modules that use the R-tree secondary access method
Design a user-defined data type
Other user-defined data type design considerations

Extending Informix®
Beyond standard relational database objects, HCL Informix® can be extended to handle specialized data types, access methods, routines, and other objects. Informix includes many built-in extensions that are fully integrated in the database server. Informix also provides DataBlade® modules, which are packages of extended database objects for a particular purpose and that are installed separately from the database server. Alternatively, you can create your own user-defined objects for Informix.
- Informix® extensions and DataBlade® modules
  These topics describe how to use built-in database extensions and separately installed DataBlade® modules.
- Creating extensions
  You can create user-defined data types, routines, access methods, and other database objects to suit your needs. You can use application programming interfaces to write user-defined routines and applications that access data in Informix® databases.
  - DataBlade® API Programmer's Guide
    The Informix® DataBlade® API Programmer's Guide describes information about the DataBlade API, the C-language application programming interface (API) provided with HCL Informix.
  - DataBlade® API Function Reference
    The Informix® DataBlade® API Function Reference describes the DataBlade API functions and the subset of Informix ESQL/C functions that the DataBlade API supports.
  - DataBlade® Developers Kit
    The DataBlade® Developers Kit (DBDK) guides contain information about the tools you can use to develop and package DataBlade modules, which extend the functionality of HCL Informix® databases.
  - J/Foundation Developer's Guide
    The J/Foundation Developer's Guide describes how to write user-defined routines (UDRs) in the Java™ programming language for Informix®.
  - R-Tree Index User's Guide
    The Informix® R-Tree Index User's Guide describes the HCL Informix R-tree secondary access method and how to access and use its components.
  - User-Defined Routines and Data Types Developer's Guide
    The Informix® User-Defined Routines and Data Types Developer's Guide describes how to define new data types and enable user-defined routines (UDRs) to extend HCL Informix.
  - Virtual-Table Interface Guide
    The Informix® Virtual-Table Interface Programmer's Guide explains how to create a primary access method with the Virtual-Table Interface (VTI) so that users have a single SQL interface to HCL Informix tables and to data that does not conform to the storage scheme of HCL Informix.
  - Virtual-Index Interface Guide
    The Informix® Virtual-Index Interface Programmer's Guide explains how to create a secondary access method with the Virtual-Index Interface (VII) to extend the built-in indexing schemes of HCL Informix typically with a DataBlade® module.

Other user-defined data type design considerations

When you design a new user-defined data type to store multidimensional data, include all the dimensions likely to be used in a query.

For example, suppose you are designing a user-defined data type to store information on beach resorts for a travel application. Because queries for resorts often include a time element, such as the time of high and low season rates for a particular resort, you might want to include a time dimension in the resort data type, as well as the usual location. When you create an R-tree index on a column of this data type, the time dimension is built into the index, and queries that specify time might execute faster.

Include dimensions that are also selective. This means that the values in a particular dimension effectively separate desired data from undesired data. For example, latitude and longitude spans are probably selective in a database of satellite photos because they can separate out just the few pictures in an area of interest from many other pictures scattered over the earth.