AWS re:Invent 2018

Amazon Relational Database Service (Amazon RDS) is a fully managed relational database service that enables you to launch an optimally configured, secure, and highly available database with just a few clicks. It manages time-consuming database administration tasks, freeing you to focus on your applications and business. We review the capabilities of the service and review the latest available featurese.

Amazon Aurora is a MySQL- and PostgreSQL-compatible relational database with the speed, reliability, and availability of commercial databases at one-tenth the cost. This session provides an overview of Aurora, explores recently announced features, such as Serverless, Multi-Master, and Performance Insights, and helps you get started.

Shawn Bice, VP of Non-Relational Databases at AWS, discusses a purpose-built strategy for databases, where you choose the right tool for the job. Shawn explains why your application should drive the requirements of a database, not the other way around. We introduce AWS databases that are purpose-built for your application use cases. Learn why you should select different database services to solve different aspects of an application, and watch a demonstration in which application use cases lend themselves well to specific data services. If you're a developer building modern applications that require high performance, scale, and functional databases, and you're trying to determine which relational and non-relational data services to use, this session is for you.

We're witnessing an unprecedented growth in the amount of data collected and stored in the cloud. Getting insights from this data requires database and analytics services that scale and perform in ways not possible before. AWS offers the broadest set of database and analytics services to process, store, manage, and analyze all your data. In this session, we provide an overview of the database and analytics services at AWS, new services and features we launched this year, how customers are using these services, and our vision for continued innovation in this space.

Learn how to convert and migrate your relational databases, nonrelational databases, and data warehouses to the cloud. AWS Database Migration Service (AWS DMS) and AWS Schema Conversion Tool (AWS SCT) can help with homogeneous migrations as well as migrations between different database engines, such as Oracle or SQL Server, to Amazon Aurora. Hear from Verizon about how they intend to migrate critical databases to Amazon Aurora with PostgreSQL compatibility from their current on-premises Oracle databases, and learn how they intend to deal with challenges such as conversion of legacy code and complex data types, supporting business resiliency, and maintaining data synchronization during the transition phase.

We have recently seen some convergence of different database technologies. Many customers are evaluating heterogeneous migrations as their database needs have evolved or changed. Evaluating the best database to use for a job isn't as clear as it was ten years ago. We'll discuss the ideal use cases for relational and nonrelational data services, including Amazon ElastiCache for Redis, Amazon DynamoDB, Amazon Aurora, Amazon Neptune, and Amazon Redshift. This session digs into how to evaluate a new workload for the best managed database option. Please join us for a speaker meet-and-greet following this session at the Speaker Lounge (ARIA East, Level 1, Willow Lounge). The meet-and-greet starts 15 minutes after the session and runs for half an hour.

In this session, we provide a behind the scenes peek to learn about the design and architecture of Amazon ElastiCache. See common design patterns with our Redis and Memcached offerings and how customers use them for in-memory data processing to reduce latency and improve application throughput. We review ElastiCache best practices, design patterns, and anti-patterns. Complete Title: AWS re:Invent 2018: [REPEAT 1] ElastiCache Deep Dive: Design Patterns for In-Memory Data Stores (DAT302-R1)

In this session, learn about the security features built into Amazon DynamoDB and how you can best use them to protect your data. We show you how customers are using the available options for controlling access to their tables and the content stored within those tables. We also show you how customers are protecting the contents of their tables with encryption, and how they monitor access to their data.

Amazon Aurora is a fully managed relational database service that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. With Aurora, we've completely reimagined how databases are built for the cloud, providing you higher performance, availability, and durability than previously possible. In this session, we dive deep into the architectural details of Aurora with MySQL compatibility, and we review recent innovations, such as parallel query, backtrack, serverless, and multi-master. We also share best practices for utilizing the power of relational databases at cloud scale.

Amazon Aurora with PostgreSQL Compatibility is a relational database service that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. We review the functionality in order to understand the architectural differences that contribute to improved scalability, availability, and durability. We also dive deep into the capabilities of the service and review the latest available features. Finally, we walk through the techniques that can be used to migrate to Amazon Aurora.