Thore Thomassen shares from experience how to combine structured data in a DWH with unstructured data in NoSQL, and using parallel data warehouse appliances to boost the analytical capabilities.
Julien Le Dem discusses the advantages of a columnar data layout, specifically the features and design choices Apache Parquet uses to achieve goals of interoperability, space and query efficiency.
James Richardson, Nat Pryce discuss some of the challenges faced using Neo4J for interactive analysis of large data imports (80K nodes, 150k relationships) and how they overcame them.
Dean Wampler takes a look at SQL’s resurgence and specific example technologies, including: NewSQL, Hybrid SQL, SQL abstractions on top of file-based data, SQL as a functional programming language.
Michael Hunger and Lorenzo Speranzoni show how easy it is to get started with Spring Data Neo4j using Spring Boot.
Eric Redmond explains the differences and commonalities amongst many kinds of databases and takes a stab at the marketing term “NoSQL.”
Stuart Sierra provides an introduction to Datomic's data model, architecture, query syntax, and transactions.
John Leach explains using HBase co-processors to support a full ANSI SQL RDBMS without modifying the core HBase source, showing how Hadoop/HBase can replace traditional RDBMS solutions.
The authors focus on POJO persistence over Cassandra, including automatic Cassandra schema generation and Spring context configuration using both XML and Java.
This talk goes over the design motivation for Zen and describe its internals including the API, type system and HBase backend.
Jayesh Thakrar shows what can be done with irb, how to exploit JRuby-Java integration, and demonstrates how the Shell can be used in Hadoop streaming to perform complex and large volume batch jobs.
This talk provides a broad overview of the new features introduced in the latest Spring Data release trains: recent additions in Spring Data Commons and the latest features of individual store modules