Fred Ho's Blog
IBM has obtained distribution rights to the following white paper published by Bloor Research (author: Philip Howard) titled "IBM Informix in hybrid workload environments". It discusses key features such as Flexible Grid, Time-Series support and Informix Warehouse Accelerator which makes Informix ideal for Analytic applications.
Query Acceleration for Business using Informix Warehouse Accelerator
A draft IBM Redbooks publication (Planned Published date of November 2013)
IBM Informix Warehouse Accelerator (IWA) is a state-of-the-art in-memory database designed to exploit affordable innovations in memory and processor technology and trends in novel ways to boost query performance. It is a disruptive technology that changes how organizations provide analytics to its operational and historical data. Informix Warehouse Accelerator leverages columnar, in-memory approach to accelerate even the most complex warehouse and operational queries without application changes or tuning.
This book provides a comprehensive look at the technology and architecture behind the system. It contains information about the tools, data synchronization, and query processing capabilities of Informix Warehouse Accelerator, and steps to implement data analysis by using Informix Warehouse Accelerator within an organization.
Table of contents
Chapter 1. Introduction to Informix Warehouse Accelerator
In-Memory Databases Go Mainstream
While much have been written about the subject, including several blog entries I have written here, it takes a database market share leader like Oracle to make it mainstream.
In the super-hyped Oracle OpenWorld event in San Francisco this week, the headline news is the announcement of Oracle 12c and the In-memory option. Several articles have already been published in the press, including:
1) Oracle Open World 2013: Oracle launches in-memory database search
2) Oracle's Ellison promises 'ungodly' database speed with new in-memory option
3) Oracle's Ellison Tries To Outmaneuver SAP Hana
Based solely on publicly available information from these articles, I will point out a few similarities as well as differences from our own offering, namely the Informix Warehouse Accelerator.
With the Informix/IWA combination, we store OLTP in its original row format in the Informix database, while in-memory processing is done using a columnar approach. Difference is that IWA never stores the columnar data on disk. HANA (from SAP), in contrast, uses only columnar storage for both OLTP/OLAP processing.
Regardless of tradeoffs between different approaches, the most important point is that customers should feel that in-memory database is no longer an esoteric technology to watch out for. It has arrived and it is now mainstream. Informix has a strong offering and it has already proven itself with customers.
Carlton Doe offers an updated 1-day Proof of Technology (PoT) on IWA.
Its objective is as follows:
In this Proof of Technology, participants will install and configure the accelerator server. They will learn how to analyze queries to determine what tables and columns should be accelerated for greater performance. Finally, using a combination of graphical and command line utilities, they will create, deploy and load marts of accelerated data. They will execute queries against both non accelerated and accelerated data to see the dramatic and exponentially better response times Informix Warehouse Accelerator provides.
For information about this PoT, contact Carlton at 972-561-6103 or email@example.com.
There are numerous Informix events around the world where IWA is discussed. An upcoming webcast (Oct 1) by one of our partners, Advanced Datatools can be found at:
In building a set of messages towards the upcoming IBM Insight (formerly IOD) conference, this blog entry is being written as part of that effort (in collaboration with IBM Marketing):
The Internet of Things is changing our world with the pervasiveness of connected sensors and devices, expanding the volume of captured data exponentially. This new computing model requires us to rethink our data management strategies in several ways. Since data is captured from numerous devices across multiple data types, succeeding in the IoT space requires the ability to securely combine structured, unstructured, Time-Series, spatial and other sensor data into a single source of intelligence. We need to make sense of this huge influx of data by aggregating and analyzing data locally, at the gateway level, to use it in meaningful ways. This can only be achieved by using an intelligent database with reliability, flexibility, performance and simplicity to handle real-time and context computing on the edge. Embedding an enterprise-level database, like Informix, coupled with the power of a warehouse accelerator, can optimize business results with speed of thought insight.
There are many ways sensor data can be used. Data can be used for real-time analytics to gain intelligence and respond to events as they happen. You can use historical analysis to look through record history for trends, analyze collections of sensors for correlation and formulate hints and suggestions based on usage and patterns. As tremendous growth opportunities emerge, so do challenges. Sensors collect and forward data for a single measurement, but consumers will have many devices and want a consolidated view. These devices generate a huge amount of data and limited space will create network and latency concerns. In addition, the variety and volume of data makes it hard to locate data and perform analytics that join different kinds of data together. Databases solve these problems when data is organized locally in a compact form that is easy to search and use. Simple SQL and JSON application development interfaces provide a flexible schema without requiring upfront definitions of their types. IBM Informix hybrid capabilities provide management of SQL and NoSQL/JSON data seamlessly, in one database.
Warehouse accelerators improve the performance of traditional data warehousing queries. In the “sensor analytics zone” within IBM’s IoT architecture, IBM Informix Warehouse Accelerator speeds complex queries for relational and Time-Series data. You can scale on a cluster and provision both IDS and IWA in the cloud to analyze much more data from different sensors and gateways. IWA can perform analytics of stored sensor data, up to 1000x faster than Time-Series alone. Informix is leading the way with unique capabilities to harness IoT data at the edge and I’ll be talking more about them at Insight 2014.