This session kicks off the Couchbase Connect Big Data track by answering some fundamental questions about the relationship between NoSQL and Hadoop. Both of these address the “big data” challenge but they target different parts of it. We’ll get concrete about where it makes sense to deploy NoSQL versus where it makes sense to deploy Hadoop. More importantly, we’ll discuss how NoSQL and Hadoop compliment each other and why they’re stronger together.
Old application? Ugly or outdated designs? High cost of maintenance? An in-depth look into our experience in using Couchbase as a catalyst to modernize a standalone software appliance into cloud-based horizontally-scalable services.
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.
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.
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!
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.
Amadeus is one of the leading IT worldwide companies in the travel industry. Amadeus operates a very demanding IT environment in term of raw performance, scalability and reliability. The presentation will include a return on experience about our Couchbase usage, and two use cases, illustrating a performance/scalability oriented application, and an infrastructure supporting ultra-high availability.
Today’s innovative software is providing new ways for industrial companies to gain a competitive advantage. But harnessing that potential from scratch isn’t easy. You need to bring together device connectivity, data integration and management, data analytics, cloud, and mobility all in a way that works seamlessly together and intuitively for all the members of your business. That’s why GE created Predix. In the connected world, GE field engineers work in places where offline is the norm. This presentation will examine how the Predix Experience engineering team built a platform for building applications for the industrial workforce and how Couchbase Mobile complements GE’s Offline First approach. We will look at what Offline First means and how the platform’s offline capabilities were replaced with Couchbase Mobile in less than 90 days.