The Role of Hybrid and Best-of-Breed Architectures in Big Data Management

With the continued increase in data over the recent years, data infrastructures are changing as well. The one-size-fits-all approach for data environments is going by the wayside due to the expanding range of data types. With the growing understanding that the world of big data is heterogeneous, businesses are now employing versatile hybrid data architectures. But while they provide the right tools for the myriad requirements of big data, hybrid architectures must be properly integrated and managed to deliver their full value.

As more and more businesses embark on the journey to create value from big data, one thing has become abundantly clear: the world of big data is heterogeneous.

To educate IT and business stakeholders on the key strategies, technology components, best practices and pitfalls to avoid when evaluating and adopting a hybrid, best-of-breed approach to big data management, Database Trends and Applications recently hosted a special roundtable webcast featuring Reiner Kappenberger, global product management, HP Security Voltage; Emma McGrattan, SVP engineering with Actian; and Ron Huizenga, ER/studio product manager for Embarcadero.

An important aspect of all types of data architectures is security and hybrid architectures are no different, according to Kappenberger, who covered various methods of data protection, including HP Format-Preserving Encryption (FPE) and HP Secure Stateless Tokenization (SST). “When typically looking at encryption for FPE, everyone normally thinks of AES styles, and that’s what people would normally understand with this type of encryption; a big block of data that is unreadable. FPE is different because it allows the data to be encrypted but still look like the original data.”

If the data is a Social Security number, it will look like a Social Security number. HP Secure Stateless Tokenization (SST) allows for the encryption of credit card information in either partial or full tokenization, Kappenberger said.

Alignment with business requirements is critical for any big data implementation, McGrattan noted. Full ANSI SQL 92 support and full ACID compliance, are necessary to enable that alignment, McGrattan noted.  Full ANSI SQL 92 support enables use of all standard BI tools and apps. “What we have within our product is a very rich language support. We can take any of off the shelf BI and analytics tools and just run them without change,” stated McGrattan. Full ACID compliance brings transactional integrity to Hadoop to prevent inaccurate results.

“We can’t focus on the technologies for technology’s sake,” said Huizenga. “We have to have a sound grounding in what we call business-driven data architecture.” The process of discovering data has changed. No longer is data coming from just within a company but from a range of sources on the outside as well. When data does come in from the outside, it tends to come in numerous data types and companies now must be prepared to work with these data types, he noted.

To watch a replay of the webinar, go here.

Image courtesy of Shutterstock. 


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