HP has expanded its’ Sharks family of converged systems, which it introduced last year, with the new purpose-built HP ConvergedSystem 300 for the Microsoft Analytics Platform.
“Customers today face challenges with sprawl, and our converged systems, which bring the full breadth of server, storage and networking together, are designed for this,” said Frances Guida, Manager of Converged Systems at HP. “We are expanding this with a converged system for the Microsoft analytics platform.”
Microsoft SQL Server is the most used database in the world. Massive amounts of data are being generated on SQL Server, and users want to link this data with other structured, unstructured or semi-structured data to gather new insights.
“This is for organisations that leverage SQL data in their environment,” Guida said. “It provides enterprises with a single view of all these environments, to remove the complexity out of data analytics.”
The HP ConvergedSystem 300 for Microsoft Analytics Platform integrates in-memory performance, a massively parallel processing data warehouse (SQL Server PDW) and Hadoop into one system. To enable and accelerate data driven decisions, the seamless integration of the data in SQL Server PDW with data in Hadoop utilises the PolyBase query technology.
“This offering is targeted at any company that has a lot of data in SQLs and want to take better advantage of it for analytics,” Guida said. “This is typically the high end of the mid-market, up to large enterprises, but it’s not the size of company that matters as much as the use case. It’s about having data in a SQL database, or, typically more than one of them.”
This is not the first collaboration between Microsoft and HP in data warehousing. It builds on HP Enterprise Data Warehouse, HP AppSystem for Parallel Data Warehouse, and of course, last year’s HP ConvergedSystem 300 for Microsoft Analytics Platform.
“This is really the third generation of collaboration between us and Microsoft here, and we are broadening the functionality of the product and extending it into a new space,” Guida said. “It can now handle both structured and unstructured data, which we couldn’t do before. That’s important in a Hadoop environment.”
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