Industry executives and experts share their predictions for 2022. Read them in this 14th annual VMblog.com series exclusive.
The Rise of the Hybrid Data Platform
By Sudhanshu Jain, VP of Product Management & Strategic Alliances, Pliops
Data is growing faster than we can comprehend. It is a massive opportunity for business – some even refer to data as the “new currency.” But realizing business intelligence in real time from such a large amount of data is a large and growing challenge for the industry. The rise of real-time data analysis is one of the hottest trends in data science, e.g., fraud-detection at point of sale, credit scoring, sentiment analysis, and geotargeted advertising.
Real-time analytics requires the preparation and formatting of data as soon as it is generated. Or in other words, data is available in different formats in real time to run various analytics engines in parallel. To address these needs, typically data is stored as-is, without any specific structure format, and made available for consumption in real time in various formats.
Today this problem is addressed by using data lakes where data is stored in various silos and wrappers are built around these silos to access the data. This architecture has several inherent disadvantages, e.g., metadata lifecycle in wrapper layers, privacy issues, islands with stranded data, increased storage/computation costs and built-in inefficiencies. To address some of these challenges, the industry is increasingly adopting in-memory hybrid data platforms with simultaneous support for transactional and analytical processing. Such platforms greatly improve the data lake’s operations. But today such hybrid data platforms are built using traditional server and storage architectures with ever-increasing memory footprints. Using such sub-optimal architectures poses challenges around infrastructure sprawl, power footprint, cost, and enormous software complexity built into the data engines powering such hybrid platforms.
In 2022, we will see hybrid data platforms optimized with purpose-built data engines for these applications, like those provided in Pliops Extreme Data Processor (XDP).
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ABOUT THE AUTHOR
Sudhanshu Jain serves as vice president of product management and strategic alliances at Pliops, where he leads product management and drives strategic partnerships for the company. Jain previously worked at VMware, where he oversaw product management of VMware’s Software-Defined Data Center (SDDC) and converged infrastructure solutions for more than a decade.
