Presentations

Interactive Data Analytics with Couchbase N1QL

Interactive Data Analytics with Couchbase N1QL

In this session we’ll discuss how Couchbase’s query language, N1QL provided Nielsen with an interactive querying capability that significantly increased our ability to gather meaningful insights into stored client data. In this session, you will learn how we gather those insights and interact with data analytics while leveraging SQL for JSON, N1QL. For context, Nielsen’s Answers on Demand (AOD) services deliver ratings data and other information for businesses in more than 100 countries. With the inflow of massive volumes of data and the requirement to deliver highly targeted results for clients, the ability to sift through datasets quickly and effectively is critical. The AOD services need to provide powerful analytics and reporting capabilities – essentially aggregations on the fly – through an on-demand big data platform. We at Nielsen turned to Couchbase to persist client report definitions, selections, and cache enabling us to sidestep many of the limitations of relational databases operating in a multitenant environment. The Couchbase solution delivered a 50 percent boost in response time by pre-indexing metadata and gave us the ability to query against the index or target specific documents with N1QL.

N1QL and SDK Support for Java, .NET, and Node.js

N1QL and SDK Support for Java, .NET, and Node.js

You’ve heard of the hot new query language called N1QL, but do you know what support is available in the official Couchbase SDKs? If not, the session is for you! In this session you will learn how to use N1QL in the SDKs. We’ll also cover the fluent DSL for Java, the Linq Provider for .NET based languages, as well as full-stack JavaScript development using the Node.js client.

Reactive Data Access with RxJava, Including N1QL

Reactive Data Access with RxJava, Including N1QL

This talk shows how to build scalable, reactive, and fault tolerant applications by making use of RxJava and the brand new fully reactive Couchbase Java SDK 2.x. We will also cover stability patterns and how our brand new query language, “N1QL” fits into the picture. This subject is important, as applications that exclusively rely on synchronous data access often hit a scalability wall when responses slow down and thread pools are exhausted. New paradigms, like reactive programming, alleviate the wasting of resources by dispatching them where they can do useful work and provide extensive toolsets to deal with the ever growing demands of web applications.

Spark with Couchbase to Electrify Your Data Processing

Spark with Couchbase to Electrify Your Data Processing

Apache Spark is a fast and general purpose engine for both large-scale data and stream processing. Mix built-in machine learning with Couchbase Server and you have a swiss army knife for real time data analytics. In this session you will learn about Apache Spark and how it fits into the Couchbase ecosystem. You will learn how to leverage core Spark components as well as higher level integrations like Spark SQL and Spark streaming. And since all talk and no play makes jack a dull boy, there will be plenty of code and demos!

Spring Data Couchbase: POJO-centric Data Access for Spring Developers

Spring Data Couchbase: POJO-centric Data Access for Spring Developers

The Spring Data project provides easy access to non-relational databases, map-reduce frameworks, and cloud-based data services. Spring Data Couchbase is part of this project and brings easy NoSQL persistence, query mechanisms and caching for Spring developers. After introducing the Spring platform and its ecosystem, we will create a simple project example showcasing the main features of Spring Data Couchbase.

Ship It! Coding Reliable Couchbase Applications to Production

Ship It! Coding Reliable Couchbase Applications to Production

Reliably delivering data to applications in a high performance way is where Couchbase shines, but maintaining a high-performance application is not just a job for Couchbase Server. Couchbase Server meets very stringent performance and availability needs, but to successfully deliver data at scale, all application components need to work together as a single system. For example, you need to be prepared for various edge conditions like expected “TMPFAIL”s, handling failovers, and dealing with higher latencies under load. Good thing you have the tools you need from the Couchbase SDK. In this session, Michael and Matt will show patterns for handling these kinds of scenarios and talk about some of the great failures from years of experience, how they can be prevented and demonstrate some techniques for making the entire system more reliable and able to recover faster.

Spark with Couchbase to Electrify Your Data Processing

Spark with Couchbase to Electrify Your Data Processing

Apache Spark is a fast and general purpose engine for both large-scale data and stream processing. Mix built-in machine learning with Couchbase Server and you have a swiss army knife for real time data analytics. In this session you will learn about Apache Spark and how it fits into the Couchbase ecosystem. You will learn how to leverage core Spark components as well as higher level integrations like Spark SQL and Spark streaming. And since all talk and no play makes jack a dull boy, there will be plenty of code and demos!