![]() With Hyper, you can really do analytics on the freshest data set. And it might be that your analytics system has a stale view on your data. If you have specialized systems, your data is in different places. Why did we do that? The answer is simple. We also focused on combining transactional systems and analytics, bringing these specialized systems together in one system to unify transactions, data ingestion, and analytics. Some of the things that followed is we optimized for in-memory processing and we took modern CPUs into account that have a lot of cores, but also are more complex. We wanted to build a relational system from the ground up, questioning the traditional design decisions and optimizing for modern hardware. With Hyper, we wanted to create something else. ![]() There were a lot of specialized systems coming-there was Hadoop, NoSQL systems, and specialized engines for transactions analytics. Traditional technologies didn’t satisfy performance and functional requirements for modern applications any longer. And when we started, there was a lot of movement in the database market. TM: Hyper started as an academic project around 10 years ago at Technical University Munich, an institution comparable to Stanford. ![]() ![]() What was the original intention of Hyper and the technology? Reference Materials Toggle sub-navigationĢ.Teams and Organizations Toggle sub-navigation.Plans and Pricing Toggle sub-navigation. ![]()
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