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How can you combine the freedom of NOSQL with the power of rich data models? Alistair looks at the good features of relational databases that we don't need to leave behind, if we choose a graph database. He then demonstrates how to model your data as a graph in Neo4j, and the kinds of queries and features that this makes possible.
In this talk MC covers the challenges of scalability, where Couchbase fits in a document database world, how Couchbase have approached the scalability issue, and how you can index and query your database using views and map/reduce queries. The presentation will include a demo of Couchbase Server, including during a scale-up situation, the challenges of the developer side of document databases, and some of the solutions that have been built using the technology.
by Richard Low
Apache Cassandra is a next generation database originally conceived at Facebook. It combines the best bits from Google's BigTable and Amazon's Dynamo papers, has a very active community, and is widely used at many large companies.
In this talk we will cover the features unique to Cassandra and explain how it achieves things such as tuneable consistency, write-optimisation, and high availability. We will discuss the strengths (and weaknesses) of Cassandra, what it is commonly used for, and how you might use it in your application.
by Malcolm Box
Live Talkback uses Cassandra to power live audience interaction on some of the biggest shows in television, including Britain's Got Talent and The X Factor. Find out why, how it works and some of the challenges in handling TV-triggered usage bursts.
by Jameel Syed
Musicmetric collects and analyses online data to present a complete picture of how people are engaging with artists online. Data is collected and combined from social media (activity timeseries, demographics), peer to peer filesharing (geographic fan activity) and reviews (NER, sentiment analysis). When we started processing increased volumes of this public data, along with private data sources such as iTunes and Spotify transactions using Hadoop we faced a new challenge; how to serve the data for hundreds of thousands of artists with our RESTful API. Of the myriad of key value stores we chose Project Voldemort. In this talk we describe our data processing pipeline and how we came to choose Voldemort.
MongoDB has found a sweet spot in enterprise adoption due to its ease of use, powerful query model and natural progression for those coming from a SQL mindset. But under the hood it has some unusual design approaches that can trip up the unwary.
Equal Experts has first hand experience of putting MongoDB to use on a number of production systems. In this talk Julian Browne will talk about the power and the pitfalls of MongoDB using practical examples that highlight its inner workings.
Spring Data makes it easier to build applications that use new data access technologies such as NoSQL databases and Hadoop. It provides a familiar and consistent Spring based programming model while retaining store-specific features and capabilities. In this talk we will focus on the Spring Data Repository abstraction that removes the need to write boiler plate code for implementing a data access layer and also provides a base level of portability across different database technologies such as JPA, MongoDB, Neo4j, and Gemfire.
I’ve learned how to build distributed systems the hard way; I’ve failed, and failed again. I’ve made many of the common mistakes and tried a few other things that turned out to be a disappointment. You shouldn't have to make those mistakes too. In this talk I'll tell the story of how I built a real time advertising analytics platform that tracks and reports on millions of impressions every day, and all the things I did wrong before I got it to work. I’ll also tell you what I did right, and the choices I don’t regret.
20th–21st September 2012