Pat Patterson and Ted Malaska talk about current and emerging data processing technologies, and the various ways of achieving "at least once" and "exactly once" timely data processing.
Andrew Psaltis talks about Apache Beam, which aims to provide a unified stream processing model for defining and executing complex data processing, data ingestion and integration workflows.
Christos Erotocritou introduces Apache Ignite, discussing how it is used to solve some of the most demanding scalability and performance challenges. He covers typical use cases and examples.
Christoph Strobl focuses on integrating search solutions like Solr, Elasticsearch as well as MongoDBs full text search into an application.
Benjamin Hindman discusses Apache Mesos, focusing on the Mesos API and how the primitives provided by Mesos can make it easier to build new stateful services and frameworks.
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.
Yann Yu discusses how Solr and Hadoop complement each other, and how to use Solr as a real-time, analytical, full-text search front-end to data stored in Hadoop.
Paco Nathan keynotes on how Spark fits into the big data landscape, describing what other systems work with Spark, and explaining why Spark is needed in the future.
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
Camille Fournier explains what projects ZooKeeper is useful for, the common challenges running it as a service and advice to consider when architecting a system using it.
In this solutions track talk, sponsored by DataStax, Johnny Miller introduces the Cassandra native protocol, native drivers and CQL, explaining how to query Cassandra without Trift or RPC.
Bikas Saha and Arun Murthy detail the design of Tez, highlighting some of its features and sharing some of the initial results obtained by Hive on Tez.