LinkedIn’s mission is to connect the world’s professionals to make them more productive and successful. LinkedIn members use the company’s products to get access to people, jobs, news, updates, and insights that help them be great at what they do. To support its goals on an engineering level, LinkedIn services must sustain high levels of QPS while providing data integrity. In this talk, we will discuss how LinkedIn uses Couchbase Server to help with read scaling and performance of its high impact services. We will also talk about some tooling we have created to integrate Couchbase Server into our systems and how we operationally manage our Couchbase Server clusters. Finally, we will explore some future uses of Couchbase Server within our environment.
Since being open sourced, Apache Kafka has been widely adopted by organizations ranging from web companies like Uber, Netflix, and LinkedIn to more traditional enterprises like Cerner, Goldman Sachs, and Cisco. These companies use Kafka in a variety of ways: 1) as a pipeline for collecting high-volume log data to load into Hadoop, 2) as a means of collecting operational metrics to feed monitoring/alerting applications, 3) for low latency messaging use cases, and 4) to power near real time stream processing. In this talk, Ewen and David will 1) discuss how companies are using Apache Kafka, 2) explore how its unique architecture enables it to be used for both real time processing and as a bus for feeding batch systems like Hadoop, and 3) describe where it fits in the Big Data ecosystem.
With NoSQL becoming an integral technology in Big Data infrastructure, the need for moving and transforming data between systems has accelerated. The Couchbase Connector for Informatica provides ETL integration that enables you to manage and transform data between Couchbase Server, a distributed elastic NoSQL document database, and any other relational or big data system.
Tableau enables people to ask questions of their data by combining analytics and visualization together with revolutionary technology. With N1QL, Tableau can now provide visual analytics to rich JSON data in Couchbase Server. In this session, you’ll learn how to pair Tableau with Couchbase Server to dramatically reduce the time-to-insight for analyzing unstructured operational data. The talk will focus on practical information such as the cycle of visual analysis, tips and tricks to drive smart and fast business insights, and interactive demos to put concepts into practice.
It’s one thing to collect a large amount user-generated data and process it. It’s another to ingest and store massive amounts of machine-generated data in real time. This session will focus on how machines and things are changing database requirements from the throughput and latency they require, to the sheer number of them, to their evolving data model, and the impact of location on network availability.
Running a site like PayPal requires both huge scale and a lot of processing to support a complex growing business. Over time, the PayPal business faces a challenge in managing the user information required to run PayPal services. By leveraging Couchbase Server, the PayPal Data Service team is able to accommodate fast access to user information at scale while streaming data into Hadoop. The solution is able to process millions of updates a minute while leveraging Kafka’s high throughput capabilities to get this user data into the Hadoop cluster.
Moody’s Analytics helps capital markets and risk management professionals worldwide respond to an evolving marketplace with confidence. Choosing the right technologies to capture, analyze and customize data is crucial to the company’s offerings. In this session, you’ll hear how we evaluated NoSQL and the challenges we faced. This presentation’s goal is to provide an overview of the nuances involved in first figuring out the problem, the challenges encountered when searching for that technology silver bullet, and ultimately where NoSQL fits into the data strategy roadmap.
Building enterprise ready customer data analysis systems can be challenging for newcomers as well as battle proven architects alike. Avalon takes the mystery out of connecting Couchbase Server into real time analytic architectures by providing a working architecture demonstrating a real world customer analysis case study. Come join Avalon as Andy and Chad take complex challenges and make them easy.
Couchbase Server and N1QL give you unprecedented power to access and analyze your data, to pick out insights, and to find trends. But to present this information, you still need a BI tool. This presentation will give a brief overview of the JDBC and ODBC drivers for Couchbase Server, along with quick demos of how to connect to popular BI tools. We will then dive more in-depth by learning how to code for both the ODBC and JDBC drivers for your own applications.
Many enterprise looking at leveraging their data with more advanced analytics turn to Spark as a standard solution. But leveraging Couchbase Server data with Spark is more simple than it looks. Databricks, founded by the creators of Spark, will present how they see Spark evolving to address new use cases, and the simple mechanisms enabling to immediately use Spark with Couchbase Server data.