Future of Database System Architectures

Over the past two decades, we have experienced major technology disruptions on multiple fronts, none bigger than the emergence of cloud computing, which has led to fundamental changes in how database software is architected. We are seeing several new trends that are similarly shaping the future of data management. With the demise of Moore's Law, we are now seeing a lot of interest (and start-ups with significant investments) in hardware database accelerators, exploring FPGAs, GPUs, and more. Economies of scale in the cloud make it possible to move to hardware many things that were done in software, the trend will continue and increase. Modern data estates are spread across data located on premises, on the edge and in one or more public clouds, spread across various sources like multiple relational databases, file and storage systems, and no-SQL systems, both operational and analytic. This phenomenon is referred to as data sprawl. We are also seeing the emergence of many novel data workloads. For example, rich data pipelines are an increasingly common workload. And finally, Machine Learning is having a rapidly increasing role in every aspect of the database software lifecycle. This SIGMOD panel will discuss the impact of the above changes and trends on database hardware and software architectures. How will these changes impact DB system design, how will DB systems look like in the near future? Where are the hardest research challenges? What learnings from the past will guide us through these disruptions?