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Amazon redshift wiki1/11/2024 It was also apparent that the rate of innovation would accelerate in the cloud. We were working with customers’ on-premises systems where it would take us several days or weeks to resolve an issue, whereas with a cloud data warehouse like Redshift, it would take minutes. Ippokratis: I was at IBM Research at the time working on database technologies there, and we recognized that providing data warehousing as a cloud service was a game changer. It was a real game-changer for this industry segment. The fact that you could provision a data warehouse in minutes instead of months also caught everyone’s attention. When we launched the service and announced our pricing at $1000 a terabyte per year, people just couldn’t believe we could offer a product with that much capability at such a low price point. This customer soon turned into one of our biggest advocates. When I heard about their challenges, I got in touch, understood their feedback, and incorporated it into the service before we made it generally available in February 2013. Another early customer was pretty unhappy with gaps in our early functionality. It was about 10 to 20 times faster than what they had been using before. One of our early private beta customers tried it and the results came back so fast they thought the system was broken. This was at a time when customers’ data volumes were exploding, and not just from relational databases, but from a wide variety of sources. So, this is what we started to build, operating under the code name Cookie Monster. Customers told us they wanted to run data warehousing at scale in the cloud, that they didn’t want to compromise on performance or functionality, and that it had to be cost-effective enough for them to analyze all of their data. They were expensive, had punitive licensing, were hard to scale, and customers couldn’t analyze all of their data. In many cases, it was the last thing they were running on premises, and they were still dealing with all of the challenges of on-premises data warehouses. Rahul: We had been meeting with customers who in the years leading up to the launch of Amazon Redshift had moved just about every workload they had to the cloud except for their data warehouse. In June a subset of the team will present the paper “ Amazon Redshift re-invented ” at a leading international forum for database researchers, practitioners, and developers, the ACM SIGMOD/PODS Conference in Philadelphia. Today, the service is used by tens of thousands of customers to process exabytes of data daily. The Redshift team has been sprinting to keep apace of customer demand ever since. If we hadn’t done that preview, we would have been caught short.” So we scrambled right after re:Invent to accelerate our hardware orders to ensure we had enough capacity on the ground for when the product became generally available in early 2013. “Within about three days we realized that we had ten times more demand for Redshift than we had planned for the entire first year of the service. “At preview we asked customers to sign up and give us some indication of their data volume and workloads,” Pathak, now vice president of Relational Engines at AWS, said. “But we didn’t really understand how popular,” he recalls. That’s why, on the day of the announcement, Rahul Pathak, then a senior product manager, and the entire Amazon Redshift team were confident the product would be popular. They saw speedups ranging from 10x – 150x!” ’s data warehouse team has been piloting Amazon Redshift and comparing it to their on-premise data warehouse for a range of representative queries against a two billion row data set. In a blog post on November 28, 2012, Werner Vogels, Amazon chief technical officer, highlighted the news: “Today, we are excited to announce the limited preview of Amazon Redshift, a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud.”įurther in the post, Vogels added, “The result of our focus on performance has been dramatic.
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