Couchbase Server’s new spatial views feature is not just there for your geospatial indexes, it can also be used to build multi-dimensional indexes on any number of metrics. Even combined indexes (e.g. number of people living in a geographic region) can be built and queried by using this feature. This talk will explain typical use cases, how to best write your map function, and how to query multi-dimensional views enabling you to write location-aware applications with Couchbase Server 4.0.
N1QL extends the power of SQL to JSON, enabling full query capabilities on Couchbase Server and removes one of the final hurdles to migration from MySQL to the flexible, scalable Couchbase Server. But in order to migrate seamlessly from MySQL to Couchbase, it is imperative to know the language and implementation differences between MySQL and N1QL. This talk will discuss various aspects of how to approach migration including: document key design, data modeling, migration options, and the language. This session will also give attendees an understanding of the different steps involved in making the decision to migrate from MySQL to Couchbase via N1QL.
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.
Couchbase Server 4.0 brings many new capabilities and features in its architecture. Couchbase’s Director of Product Management, Cihan Biyikoglu will look at the Couchbase Server 4.0 architecture in detail and provide attendees with an understanding of how the cluster manager, cache engine, and storage engine plug together with the data, query and index services to give you a best of breed NoSQL engine for big data processing. This is the grand tour of Couchbase Server 4.0 so this is the session for you if you are a master architect, developer or administrator of platforms.
We’re all familiar with modeling data the relational way. When we move to a document database we need to think about things a little differently. In this talk we’ll look how best to plan, model and maintain your data using a document database. By diving into real world case studies of Couchbase users, we’ll look at the three main things you need to know about modeling your data in a document database: document design, key design and querying.
B+-tree has been used as one of the main index structures in database fields for more than four decades. However, with the unprecedented amount of data being generated by modern, global-scale web, mobile, and IoT applications, typical B+-tree implementations are beginning to show scalability and performance issues. Various key-value storage engines with variants of B+-tree such as log-structured merge tree (LSM-tree), have been proposed to address these limitations. At Couchbase, we have been working on a new key-value storage engine, ForestDB, that has a main index structure based on Hierarchical B+- Tree (based Trie or HB+-Trie). and provides high scalability and performance. In this presentation, we introduce ForestDB and discuss why ForestDB is a good fit for modern big data applications.
MongoDB has been the default database choice in the Node.js world for too long. That’s largely been thanks to the Mongoose ODM, which makes it simple to create an MVC pattern application with some of the same abstraction you’d get from a full framework such as Rails. Now that we have the Ottoman ODM for Couchbase, it’s far easier to build Node.js apps backed by Couchbase. In this talk, I’ll show how to build a simple Node.js application that follows the MVC pattern. At first I’ll start out using the Node.js client directly, both through key-value access and with N1QL, and then I’ll switch to using Ottoman to show just how effortless it can be to use Couchbase Server in your Node.js applications.
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.