5 min
HPE Vertica holds an enviable position in the big data world, an early entrant with one of the largest installed user bases and a leader in MPP architecture, it has quickly risen to the top tier of EDW technology. The column-oriented, highly scalable analytical database was built to address the most demanding big data analytics initiatives. There are plenty of proof points of HPE Vertica analytics capabilities. One of the most advanced SQL databases, HPE Vertica supports high degree of concurrency and parallelism, advanced compression capabilities, cloud integration and In-Database machine learning resulting in enhanced performance at scale.
Businesses today, such as social media giant Facebook, ICICI Bank, Aircel and MTS, among other leading heavyweights, rely heavily on HPE Vertica 8 to answer some of the most business-critical questions. The platform gives the businesses the capabilities to conduct sophisticated analysis at “industry-leading” scale and speed, regardless of where their data lives.
The database management market is rife with competition and HPE has a definitive lead in big data platform vendor list dominated by Oracle, IBM and Teradata. To add to that, HPE has a clutch of big name customers [Cardlytics, Chase, AT&T, WebMD] in its corner to stave off competition from big data vendors and cloud-based analytics service providers AWS, Azure and Google Compute Engine. With flexible deployments, HPE has targeted the right customers who don’t want to control their infrastructure and not ship all the data into the cloud. The strategy seems to have paid off well.
Vertica is a mature solution, designed for complex, query-intensive applications and has a definitive edge over Hadoop-SQL combinations. With user-friendly features being the name of the game, HPE Vertica is definitely going where its customers are and solving performance challenges that business environments face today. For years, it was all about having more and more data but gradually, there are more concurrent users and competing, simultaneous workloads going on.
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