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Over the last few years, new business demands – from digital transformation to improving the customer experience – have overwhelmed existing SQL infrastructure. The increase in interactions through new Web and mobile apps and their underlying APIs are creating massive volumes of queries and transactions that are overloading existing databases. Improving the customer experience requires performing real-time analytics and automation during transactions and interactions, not after. Traditional data warehouses and other related tools cannot address these needs because, by design, they work on a copy of the data that is almost immediately out of data as it is extracted, transformed and loaded (ETL) from operational systems. They also don’t support the new analytical approaches, from stream processing to artificial intelligence, needed for these new initiatives.
The good news is that several companies have successfully implemented these new approaches to real-time analytics with the GridGain® in-memory computing platform. Download this Application Note and learn GridGain adds speed, scalability, and in-memory computing to SQL.