Teradata rolls out platform updates designed to connect Hadoop ecosystem

The data-warehousing provider introduced the Teradata Data Warehouse Appliance 2800, expanded Teradata QueryGrid integrations, and an enhancement to the Teradata database.  Read about it here on +ZDNet

Teradata, MapR Unite Hadoop and Data Warehouses

Big Data technologies like Hadoop and NoSQL could be coming to a data warehouse near you -- thanks to Teradata and MapR. The two companies have inked a partnership to ensure MapR's Hadoop and NoSQL capabilities integrate with Teradata's data warehousing portfolio.

Article from +Information Management

Teradata has acquired Revelytix and Hadapt

It appears that there is some consolidation in the big data market following the news that Teradata has acquired Revelytix and Hadapt.

Teradata's fast track to Big Data analytics

In this blog post on +Information Management by +Ventana Research's Tony Cosentino he looks at the progress Teradata has made in their am to parallelise R on their Aster Discovery platform.

I'm glad it's already in Beta - it would be a wonderful thing to see R running against a Teradata database.  It makes me smile just thinking of the kinds of analyses that could be possible.

Teradata takes a bigger approach to Big Data

This article  from +Information Management written by Mark Smith of +Ventana Research looks at the steps +Teradata  have taken to bring them into line more with Big Data.

I like the fact that Teradata has advanced its data warehouse appliance and database technologies to unify in-memory and distributed computing with Hadoop, other databases and NoSQL in one architecture - that places them perfectly for the Big Data Market.

Teradata 15 and Query Grid

This +TDWI  article by Stephen Swoyer goes though Teradata 15 and it's Query Grid functionality.  In the article he points out that Query Grid is not going to be around until Q3 of this year.

It sounds great and definitely the way to go with big data efficiency is to push the processing down to where the data is.  I just wonder whether this is going to be a multi phase implementation as it's going to take time to put all this into place.

MapReduce - the concept behind Big Data. Links to resources and a summary of what it actually is.

Here is the link to the Google Research Publication on MapReduce.
Link to the Wikipedia page on MapReduce.
There is also an extensive set of documentation about MapReduce here.

Essentially the data has a MAP function (filter and sort) performed on it then a REDUCE (summary) function performed on the result of the MAP function.  It uses parallel processing to do these  (a bit like a multi level tree structure) controlled by a framework which makes it quick, increases fault tolerance and reduces redundancy.  This is very similar to the structure of queries in Teradata using AMPS where one AMP controls the entire query.

The possibilities of this approach to me are exciting as it enables us to process large amounts of data in a short amount of time and give an end result that is worthwhile.

On-demand Analysis vs Real-time Data and when it is needed

On-demand analysis is increasingly needed as we strive to get a competitive edge over rivals or adhere to auditing or regulations.

In this TDWI White Paper Cirro describe scenarios for providing the ability to do on-demand analysis and the potential solutions and costs involved.

Cirro's Data Hub enables you to write a single query that then splits into queries per data source and then knit them back together.  A bit like in Teradata when a query is shared across all amps and then brought together by the controlling amp at the end.

Many people confuse on-demand analysis and real-time data in their mind.

Real-time data can be very expensive to provide for analysis and thought should be taken into if it is necessary.  This TDWI Article David Stodder discusses when it is the right time for using data real-time.  I think his point 3 is very important (Don't assume that application business rules can handle real time).

Teradata Database release 15 allows language choice

The latest release of Teradata allows a choice of language to query the database as well as the standard SQL.  The ones I'm most excited about are:

• Java
• Perl
• Ruby
• Python
• R

Here is a link to the guide for TeradataR  - TeradataR 1.0.1 Guide

It also provides support for XML, JSON and weblog data.  This means that Java and most internet based code can use Teradata data seamlessly due to the object similarities.

Finally support is added for solid state drives.

Teradata Release 15 Teradata 15