Welcome
Data warehousing
In addition to designing and implementing Informix® dimensional databases, you can use tools to create data warehouse applications and optimize your data warehouse queries.
Informix® Warehouse Accelerator
Data marts and AQTs
For efficient query processing, the accelerator server must have its own copy of the data. The data is stored in logical collections of related data, or data marts. A data mart specifies the collection of tables that are loaded into an accelerator and the relationships, or references, between these tables.
Create a data mart
After you configure the accelerator server and set up the connection between an accelerator and the database server, you need to create the data marts.
Creating data mart definitions by using Informix® Smart Analytics Optimizer Studio
You can use Smart Analytics Optimizer Studio to create the data mart definitions when you are familiar with the database schema and the application queries that are sent to the database server.
Fact table for the data mart
Typical queries against a data mart join the fact table with the dimension tables and group information by a specific criteria.

HCL Informix® V15.0 documentation
Welcome to the documentation for HCL Informix® 15.0 and related client tools and products.
Product overview
HCL Informix® is a fast and scalable database server that manages traditional relational, object-relational, and dimensional databases. Its small footprint and self-managing capabilities are suited to embedded data-management solutions.
Installing
These topics describe how to install HCL Informix® database servers, client products, and DataBlade® modules.
Administering
In addition to administering the database server, you can tune performance, replicate data, and archive data.
Migrating and upgrading
You can upgrade to the 15.0 release of HCL Informix® or migrate from other database servers to Informix. Upgrading is an in-place migration method that uses your existing hardware and operating system software. Some changes to the Informix database server can affect upgrading from a previous release.
Client APIs and tools
You can use the HCL Informix® implementation of client APIs to develop applications for Informix database servers.
Embedding Informix®
When you embed HCL Informix®, you can use enterprise-class high-availability and high performance with embeddability features such as easy programmability, a small disk and memory footprint, and silent deployment.
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.
Data warehousing
In addition to designing and implementing Informix® dimensional databases, you can use tools to create data warehouse applications and optimize your data warehouse queries.
- Dimensional databases
  These topics provide information to help you design, implement, and manage dimensional databases, and describes the tools that you can use to create data warehouses and optimize your data warehouse queries.
- Informix® Warehouse Accelerator
  - Overview of Informix® Warehouse Accelerator
    Informix® Warehouse Accelerator is a product that you use to improve the performance of your warehouse queries.
  - Installation
    You can install Informix® Warehouse Accelerator on the same computer as the Informix database server, on a separate computer, or on a cluster (including a high-availability cluster).
  - Configuration
    You must configure the accelerator server to work with the Informix® database server.
  - Create an accelerator
    You create an accelerator by connecting the Informix® database server to the accelerator server.
  - Data marts and AQTs
    For efficient query processing, the accelerator server must have its own copy of the data. The data is stored in logical collections of related data, or data marts. A data mart specifies the collection of tables that are loaded into an accelerator and the relationships, or references, between these tables.
    - Accelerated query tables
      Accelerated query tables, or AQTs, store information about data marts that the database server uses to determine which queries can be processed by Informix® Warehouse Accelerator.
    - Data marts
      Typically, data marts contain a subset of the tables in your database. The data marts can also contain a subset of the columns within a table. This configuration is advantageous when you are using the TCP/IP loopback optimization between Informix® and IWA, because it provides a seamless experience for the customer.
    - Create a data mart
      After you configure the accelerator server and set up the connection between an accelerator and the database server, you need to create the data marts.
      - Workload analysis
        Workload analysis is a process of designing an effective data mart.
      - Creating data mart definitions manually by using workload analysis
        Workload analysis involves two main steps, gathering information about your query workload, which is known as query probing, and analysis of the query probing data.
      - Creating data mart definitions by using Informix® Smart Analytics Optimizer Studio
        You can use Smart Analytics Optimizer Studio to create the data mart definitions when you are familiar with the database schema and the application queries that are sent to the database server.
        References in data marts
        A reference is a join between two database tables that indicates how the tables in the data mart are related to each other.
        Join tables at run time
        When you specify that the tables are joined at run time, the tables are joined in the system memory of the accelerator server when the query is run.
        Fact table for the data mart
        Typical queries against a data mart join the fact table with the dimension tables and group information by a specific criteria.
    - Deploy and load the data mart
      To deploy a data mart, you specify the accelerator that will contain the data mart definition file. When you load a data mart, the related data is unloaded from the Informix® tables and transferred to the accelerator server.
    - Update a data mart
      You can refresh the data in a data mart by re-creating the data mart or by dropping and loading the data in a partition or in a fact or dimension table. You can refresh the data in a data mart. You can update the data mart definition when you change the warehouse schema.
    - Managing a data mart
      You might need to drop or re-create a data mart, for example, if the schema of the underlying tables is changed, or if you create a new data mart and need to remove an old data mart.
    - Drop a data mart
      You can drop a data mart if you no longer need the data mart or if you need to update the data in a data mart.
  - Data marts and AQTs
    For efficient query processing, the accelerator server must have its own copy of the data. The data is stored in logical collections of related data, or data marts. A data mart specifies the collection of tables that are loaded into an accelerator and the relationships, or references, between these tables.
  - Turning on query acceleration
    Before queries can be routed to the accelerator server for processing, you must set the use_dwa session environment variable.
  - SQL administration routines
    You can use the Informix® Warehouse Accelerator functions and procedures from the command line or in an application to automate administration tasks.
  - Reversion requirements for an Informix® warehouse server and Informix® Warehouse Accelerator
    If you revert the HCL Informix® server to an earlier version, you must drop all of the data marts. If you created data mart definitions by using workload analysis, you must drop all of the tables that were created by the probe2Mart() procedure.
  - Troubleshooting
  - Sample warehouse schema
    The Informix® Warehouse Accelerator examples use this sample warehouse schema.
  - Sysmaster interface (SMI) pseudo tables for query probing data
    The SMI tables provide a way to access probing data in a relational form, which is most convenient for further processing.
  - Supported locales
    Informix® Warehouse Accelerator supports a subset of the locales that HCL Informix supports.
Designing databases
The first step in creating a relational database is to construct a data model, which is a precise, complete definition of the data you want to store. After you prepare your data model, you must implement it as a database and tables. To implement your data model, you first select a data type for each column and then you create a database and tables and populate the tables with data. You can also implement fragmentation strategies and control access to your data.
JSON compatibility
You can use the popular JSON-oriented query language created by MongoDB to interact with data stored in HCL Informix®.
Security
You can secure your Informix® database server and the data that is stored in your Informix databases. You can encrypt data, secure connections, control user privileges and access, and audit data security.
SQL programming
You can use the HCL Informix® implementation of the SQL language to develop applications for Informix database servers.
Troubleshooting HCL Informix®
Several troubleshooting techniques, tools, and resources are available for resolving problems that you encounter in your HCL Informix® database server environment.

Fact table for the data mart

Typical queries against a data mart join the fact table with the dimension tables and group information by a specific criteria.

When you specify the tables to use for the data mart, Informix® Smart Analytics Optimizer Studio automatically identifies the fact table in the warehouse on the Informix® database server. The fact table is partitioned across the worker nodes of the accelerator server to reach a maximum degree of parallel processing.

The fact table for the data mart does not necessarily need to be the fact table in the warehouse that you created on the Informix® database server.

By default, the largest table that you identify for the data mart is designated as the fact table by Informix® Smart Analytics Optimizer Studio. However, you can specify any table that is part of a star or snowflake schema as the fact table for a data mart.