cloud

Big Data Architectural Patterns and Best Practices

The world is producing an ever increasing volume, velocity, and variety of big data. Consumers and businesses are demanding up-to-the-second (or even millisecond) analytics on their fast-moving data, in addition to classic batch processing. AWS delivers many technologies for solving big data problems. But what services should you use, why, when, and how?

Data + Cloud: What Does It All Mean?

Big Data. Fast Data. NoSQL. NewSQL. We’ve experienced something of a renaissance in the storage and processing of data in the last decade of computing after years of “Relational Winter.” We’re now entering into the next phase of this evolution: the convergence of data and the cloud.

Running NuoDB on Google Compute Engine

Meet engineers from NuoDB: an elastically scalable SQL database built for the cloud. We will learn about their approach to distributed SQL databases and get a live demo. We’ll cover the steps they took to get NuoDB running on Google Compute Engine, talk about how they evaluate infrastructure (both physical hardware and cloud), and reveal …

Running NuoDB on Google Compute Engine Read More »

Where Is My Data?

A look at data storage options in Microsoft Azure cloud platform, discussing the pros and cons of each one and how to use them all together for the best results.

Amazon RDS for Microsoft SQL Server

Learn how to architect high-performance applications and production workloads using Amazon RDS for SQL Server. Understand how to migrate your data to an Amazon RDS instance, apply security best practices, and optimize your database instance and applications for high availability.

Changing Database & Datacenter at Lanyrd.com

As is the case for many websites and applications, when the size of its users reach a certain point, critical changes to the architecture must be made. This presentation discusses how Lanyrd addressed this problem, when they decided to move from MySQL to PostgreSQL, and from AWS to Softlayer.