AWS re:Invent 2016

Learn from AWS and Sony DADC how the transformation in content aggregation, management, and delivery are optimized with Sony Ven.ue; a Media as a Service (MaaS) offering. In this session, you learn about the Ven.ue architecture, which uses end-to-end AWS services for content preparation, protection, management, and global content delivery. We dive deep on the integrations with AWS that make Amazon CloudFront a core component of the Ven.ue service. You also hear from a customer of Sony Ven.ue, Funimation, on how they benefit from this platform.

Under Armour implemented cross-region replication with Amazon DynamoDB Streams. Come listen as they share the keys to success.

Amazon Redshift is a fast, simple, cost-effective data warehousing solution, and in this session, we look at the tools and techniques you can use to migrate your existing data warehouse to Amazon Redshift. We will then present a case study on Scholastic’s migration to Amazon Redshift. Scholastic, a large 100-year-old publishing company, was running their business with older, on-premise, data warehousing and analytics solutions, which could not keep up with business needs and were expensive. Scholastic also needed to include new capabilities like streaming data and real time analytics. Scholastic migrated to Amazon Redshift, and achieved agility and faster time to insight while dramatically reducing costs. In this session, Scholastic will discuss how they achieved this, including options considered, technical architecture implemented, results, and lessons learned.

Amazon Aurora is a MySQL-compatible relational database engine with the speed, reliability, and availability of high-end commercial databases at one-tenth the cost. This session introduces you to Amazon Aurora, explores the capabilities and features of Aurora, explains common use cases, and helps you get started with Aurora. Debanjan Saha, general manager for Aurora, explains how Aurora differs from other commonly available databases while staying compatible with MySQL and providing a high-end, cost-effective alternative to commercial and open-source database engines. In addition, Linda Xu, data architect at Ticketmaster, walks you through Ticketmaster's journey to Amazon Aurora, starting with evaluation through production migration of a critical Ticketmaster database to Amazon Aurora. Ticketmaster is one of the world's top 10 e-commerce companies and the global market leader in ticketing. In this session, Linda discusses how Aurora lets Ticketmaster provide better services to their fans, customers, and clients, and helps reduce the cost and operational burden while giving greater flexibility to support heavy traffic spikes.

Mass spectrometry is the gold standard for determining chemical compositions, with spectrometers often measuring the mass of a compound down to a single electron. This level of granularity produces an enormous amount of hierarchical data that doesn't fit well into rows and columns. In this talk, learn how Thermo Fisher is using MongoDB Atlas on AWS to allow their users to get near real-time insights from mass spectrometry experiments—a process that used to take days. We also share how the underlying database service used by Thermo Fisher was built on AWS.

Learn how the AWS Marketplace brings together customers who have challenges with ISVs who have solutions to those challenges. See how to use relational and NoSQL technologies on AWS to build enterprise and consumer apps. NBC used MarkLogic to deliver an award-winning app that can handle high traffic levels and unexpected usage spikes. NBC’s popular, Emmy-winning, “SNL 40” was launched to celebrate the 40th anniversary of Saturday Night Live, and delivers four decades of sketches and performances. Hosted on AWS, the app — as well as a browser-based platform — are powered by the MarkLogic Enterprise NoSQL database. Come learn from the team who collaborated on this project how to run your own database on AWS, and how to integrate with Amazon RDS and other data stores. A world-recognized automotive brand needed to deliver real-time response about their worldwide fleet vehicles. You will learn how they used a combination of AWS services and FileMaker Cloud, (an Apple subsidiary, procured through AWS Marketplace) to deliver high-scale dealer-facing applications.

After we launched Amazon Aurora, a cloud-native relational database with region-wide durability, high availability, fast failover, up to 15 read replicas, and up to five times the performance of MySQL, many of you asked us whether we could deliver the same features - but with PostgreSQL compatibility. We are now delivering a preview of Amazon Aurora with this functionality: we have built a PostgreSQL-compatible edition of Amazon Aurora, sharing the core Amazon Aurora innovations with the object-oriented capabilities, language interfaces, JSON compatibility, ANSI:SQL:2008 compliance, and broad functional richness of PostgreSQL. Amazon Aurora will provide full PostgreSQL compatibility while delivering more than twice the performance of the community PostgreSQL database on many workloads. At this session, we will be discussing the newest addition to Amazon Aurora in detail.

Join the principal engineer of Citus Cloud for a brief overview of Citus, best use cases for it, and a drill down into how it's run and managed as a hosted service on top of AWS. The orchestration of Citus is homegrown, but comes from years of experience of running millions of PostgreSQL databases on top of AWS. Even if you aren't looking to leverage Citus to help you scale out, in this session you'll gain insights applicable to running and managing your stateful services on top of AWS. Citus is a PostgreSQL extension that transforms the database into a distributed, horizontally scalable database. Companies like Cloudflare use Citus to process 40 TB per day. With Citus MX, applications can take advantage of every node in the cluster for writes and yielding near-linear write scaling. Citus MX provide up to 500,000 durable writes per second.

For many organizations, capturing a window of opportunity is their differentiator in the market. They invest in real-time systems to understand and respond to events. With so many use cases, it can be challenging for people to know how to invest in the right platform, and how to build in a cost-optimized way. In this session, we look at how some AWS customers are using real-time analytics to capture windows of opportunity: a telco with a major promotion, an advertising retargeter with global demands, and a personal IOT provider with a lifestyle solution. We dig deeper into their architecture and look for common patterns that can be used to build a real-time analytics platform in a cost-optimized way. We even see how a light-load, real-time analytics system can be built for less than $1000.

Amazon Aurora is a fully managed relational database engine that provides higher performance, availability and durability than previously possible using conventional monolithic database architectures. After launching a year ago, we continued adding many new features and capabilities to Aurora. In this session AWS Aurora experts will discuss the best practices that will help you put these capabilities to the best use. You will also hear from Amazon Aurora customer Intercom on the best practices they adopted for moving live databases with over two billion rows to a new datastore in Amazon Aurora with almost no downtime or lost records.