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Rick van der Lans

Welcome to my blog where I will talk about a variety of topics related to data warehousing, business intelligence, application integration, and database technology. Currently my special interests include data virtualization, NoSQL technology, and service-oriented architectures. If there are any topics you'd like me to address, send them to me at rick@r20.nl.

About the author >

Rick is an independent consultant, speaker and author, specializing in data warehousing, business intelligence, database technology and data virtualization. He is managing director and founder of R20/Consultancy. An internationally acclaimed speaker who has lectured worldwide for the last 25 years, he is the chairman of the successful annual European Enterprise Data and Business Intelligence Conference held annually in London. In the summer of 2012 he published his new book Data Virtualization for Business Intelligence Systems. He is also the author of one of the most successful books on SQL, the popular Introduction to SQL, which is available in English, Chinese, Dutch, Italian and German. He has written many white papers for various software vendors. Rick can be contacted by sending an email to rick@r20.nl.

Editor's Note: Rick's blog and more articles can be accessed through his BeyeNETWORK Expert Channel.

October 2014 Archives

Database servers come in all sizes and shapes. In fact, so many database servers have already been developed the last fifty years, that it looks almost impossible to develop a revolutionary new one. But it can be done. The last few years have proven that by thinking out-of-the-box, new promising and unique products can be developed.

One of these new kids on the block is Snowflake Elastic Data Warehouse by Snowflake Computing. It's not available yet, we still have to wait until the first half of 2015, but information is available and beta versions can be downloaded.

Defining and classifying Snowflake with one term is not that easy. Not even with two terms. To start, it's a SQL database server that supports a rich SQL dialect. It's not specifically designed for big data environments (the word doesn't even appear on the website), but to develop large data warehouses. In this respect, it competes with other so-called analytical SQL database servers.

But the most distinguishing factor is undoubtedly that it's architected from the ground up to fully exploit the cloud. This means two things, one, it's not an existing SQL database server that has been ported to the cloud, but its internal architecture is designed specifically for the cloud. All the lines of codes are new, no existing open source database server is used and adapted. It makes Snowflake highly scalable and really elastic, which is why organizations turn to the cloud.

Second, it also means that the product can really be used as a service. It only requires a minimal amount of DBA work. So, the term service doesn't only mean that it offers a service-based API, such as REST or JDBC, but that the product has been designed to operate hassle-free. Almost all the tuning and optimization is done automatically.

In case you want to know, no, the name has no relationship with the data modeling concept called snowflake schema. The name snowflake has been selected because many of the founders and developers have a strong relationship with skiing and snow.

Snowflake is a product to keep an eye on. I am looking forward to its general availability. Let's see if there is room for another database server. If it's sufficiently unique, there may well be.

Posted October 29, 2014 2:20 AM
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Many products are easy to categorize. It's a database server, an ETL tool, a reporting tool, and so on. But not every product. One such product is Pneuron. Initially you would say it's a jack of all trades, a Swiss army knife, but it isn't.

Pneuron is a platform that offers distributed data and application integration, data preparation, and analytical processing. With its workflow-like environment, a process can be defined to extract data from databases and applications, to perform analytics natively or to invoke different types of analytical applications and data integration tools, and to deliver final results to any number of destinations, or to simply persist the results so that other tools can easily access them.

Pneuron's secret is its ability to design and deploy distributed processing networks, which are based on (p)neurons (hence the product name). Each pneuron represents a task, such as data extraction, data preparation, or data analysis. Pneurons can run across a network of machines, and are, if possible, executed in parallel. It reuses the investment that companies have already made in ERP applications, ETL tools, and existing BI systems. It remains agnostic to and coordinates the use of all those prior investments.

Still, Pneuron remains hard to clarify. It's quite unique in its sort. But whatever the category is, Pneuron is worth checking out.

Posted October 28, 2014 10:03 AM
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On October 20, 2104, Teradata announced significant enhancements to QueryGrid at their Partners event in Nashville, Tennessee. QueryGrid allows developers of the Teradata database engine to transparently access data stored in Hadoop, Oracle, and Teradata Aster Database. Users won't really notice that data is not stored in Teradata's own database, but in one of the other data stores.

The same applies to developers using the Teradata Aster database. With QueryGrid they can access and manipulate data stored in Hadoop and the Teradata Database.

With QueryGrid, for both Teradata's database servers, access to big data stored in Hadoop becomes even more transparent than with its forerunner SQL-H. QueryGrid allows Teradata and Aster developers to seamlessly work with big data stored in Hadoop without the need to learn the complex Hadoop APIs.

QueryGrid is a data federator, so data from multiple data stores can be joined together. However, it's not a traditional data federator. Most data federators sit between the applications and the data stores that are being federated. It's the data federator that is being accessed by the applications. QueryGrid sits between, on one hand, the Teradata database or the Aster database, and, on the other hand, Hadoop, Oracle, and the Teradata database and the Aster database. So, applications do not directly access QueryGrid.

QueryGrid supports all the standard features one expects from a data federator. What's special about QueryGrid is that it's deeply integrated with Teradata and Aster. For example, developers using Teradata can specify one of the pre-built analytical functions supported by the Aster database, such as sessionization and connection analytics. The Teradata Database will recognize the use of this special function, knows it's supported by Aster, and automatically passes the processing of the function to Aster. In addition, if the data to be processed is not stored in Aster, but, for example, in Teradata, the relevant data is transported to Aster so that the function can be executed. This means that, due to QueryGrid, functionality of one of the Teradata database servers becomes available for the other.

QueryGrid is definitely an enrichment for organizations that want to develop big data systems by deploying the right data storage technology for the right data.

Posted October 28, 2014 9:59 AM
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