Five Reasons Scale-Out SQL Will Make Waves in the Enterprise

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Google and Facebook say so 

After two years of FUD that "SQL doesn't scale" by NoSQL evangelists, companies are finally realizing the benefits of SQL. Both Google and Facebook recently published research to show not only that SQL can scale, but that it is the best approach for certain workloads. For example, Google's F1 SQL database for Adwords enables much simpler application development for very high concurrency OLTP and OLAP workloads, saving those pricy engineers for truly valuable work. And Facebook's comments that relational databases are essential for analytics adds fuel to the hype of SQL add-ons now being promoted by every major Hadoop distribution.  

We’re quickly moving toward a world where business-relevant data analysis will support the fast moving, dynamic customer data from operational and social media interactions. Enterprises will want to analyze and act on this new breed of dynamic data in real time.

Such scale-out data management platforms need to handle large data volumes that change with high velocity and can run on commodity cloud or converged infrastructures. The options range from NoSQL and NewSQL to Hadoop. Each of these solves different data and workload challenges so the enterprise architect will need to be savvy in how to use these new building blocks successfully.

But one thing is clear – next-generation SQL databases are here to stay.

However, in-memory or scale-up databases alone will significantly drive up costs. Employing a scale-out database solution with a smart combination of RAM and flash delivers on these benefits with commodity economics.

In this slideshow, Clustrix, provider of a leading scale-out SQL database engineered for the cloud, will discuss five reasons why SQL, or rather, next-generation scale-out SQL, will make waves in the enterprise for years to come.


Related Topics : Business Intelligence Vendors, Data Quality, Data Warehousing, Key Performance Indicators, Knowledge Management

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