Abstract:

The impact that NoSQL has had on the technology community cannot be overstated. The proliferation of new and exciting data systems has led to a slew of interesting solutions to problems that were once solved the relational way. In this session we explore all that is great and good about NoSQL: the innovative software, the clever storage paradigms and the reigniting of developer interest in data access. It is unfortunate that NoSQL is not only a force for good in our community. We'll explore some of the darker corners of NoSQL: the disregard for years of proven technology, the overbearing hype, the overblown marketing and the ever present arguments over which technology is best. We close the session by exploring what can be done to extract even more value from the NoSQL movement, where we can improve how the community interacts with the larger technology community and what the future holds for data access technologies.

Abstract:

Come to this deep dive on how Pivotal's Data Lake Vision is evolving by embracing next generation in-memory data exchange and compute technologies around Spark and Tachyon. Did we say Hadoop, SQL, and what's the shortest path to get from past to future state? The next generation of data lake technology will leverage the availability of in-memory processing, with an architecture that supports multiple data analytics workloads within a single environment: SQL, R, Spark, batch and transactional.

Abstract:

When deploying your service to Microsoft Azure, you have a number of options in terms of noSQL: you can install databases on Linux or Windows virtual machines by yourself, or via the marketplace, or you can use open source databases available as a service like HBase or proprietary and managed databases like Document DB. After showing these options, we'll show Document DB in more details. This is a noSQL database as a service that stores JSON.

Abstract:

There is many frameworks that can offer real time on top of Hadoop. This talk will show you the usage of Pivotal HAWQ and how it is easy to use SQL for querying your Hadoop data. Come and see the power and easy of use that can help you on using the Hadoop ecosystem.

Abstract:

At Booking.com, we have a constant flow of events coming from various applications and internal subsystems. This critical data needs to be stored for real-time, medium and long term analysis. Events are schema-less, making it difficult to use standard analysis tools.This presentation will explain how we built a storage and analysis solution based on Riak. The talk will cover: data aggregation and serialization, Riak configuration, solutions for lowering the network usage, and finally, how Riak's advanced features are used to perform real-time data crunching on the cluster nodes.

Abstract:

How do you mix SQL and NoSQL worlds without starting a messy revolution?This live coding talk will show you how to add Elasticsearch to your legacy application without changing all your current development habits. Your application will have suddenly have advanced search features, all without the need to write complex SQL code!David will start from a Spring, Hibernate and Postgresql based application and will add a complete integration of Elasticsearch, all live from the stage during his presentation.

Abstract:

Apache Spark is a general data processing framework which allows you perform map-reduce tasks (but not only) in memory. Apache Cassandra is a highly available and massively scalable NoSQL data-store. By combining Spark flexible API and Cassandra performance, we get an interesting alternative to the Hadoop eco-system for both real-time and batch processing. During this talk we will highlight the tight integration between Spark & Cassandra and demonstrate some usages with live code demo.

Abstract:

Want to understand what persistence to NoSQL means in a Java architecture? Read on.Java is an object oriented kingdom where ORMs have flourished. Do ORMs still provide benefits in a NoSQL and polyglot era? As a side effect we will discuss the why and how of data design in NoSQL.Busted, plausible or confirmed? Here is a list of non exclusive myths and preconceptions we will explore:Once you have chosen a NoSQL product, you don't need any other.NoSQL is a data duplication nightmare.JPA is not suited to non relational databases.Objects don't fit in the data structures of NoSQL solutions.ORMs cannot abstract the underlying NoSQL models.ORMs speeds things up at runtime.The query language of NoSQL cannot be abstracted.You need access to the native API to make real use of NoSQL.ORMs don’t bring much value in an NoSQL world.And more.While we can't do explosions experiments due to fire safety regulations, your vocal contribution is encouraged. Come and debate!Note: we mention ORMs but it should really be OXMs or ONMs :)

Abstract:

How do you monitor performance for one of your clients on a specific user segmentation when dealing with billions of events a day ? With over 2 billion ads served and 230Tb of data processed a day, we at Criteo have a comprehensive need for an interactive analytics stack. And by interactive, we mean a querying system with dynamic filtering to drill down over multiple dimensions, answering within sub-second latency. This session will take you on our journey with Druid, ""an open-source data store designed for real-time exploratory analytics on large data sets"". We will explore Druid's architecture and noticeable concepts, how relevant they are for some use cases and how it really performs.

Abstract:

In this lightning talk we'll survey the developer experience of using DynamoDB, MongoDB, Cassandra, and Postgres (hstore). What languages do they work best with? Which has the best query API? What's the easiest to use from a developer perspective. I'll share my (as objective as possible) analysis and my opinions. You can draw your own conclusions!

Abstract:

Postgres SQL is a plain old SQL DB. Very powerful and very consistent, in some case, project needs an ACID database, but schemaless… With JSON support, postgres is a very interesting tool to provide ACID and some very interesting function (time management, localisation function and data types...) and the schemaless noSQL point of view with json and indexed json. This talk show some great usage and some insigth to build some great application with postgres.

Abstract:

What if we would try to make Elasticsearch SQL 92 compliant (http://www.contrib.andrew.cmu.edu/~shadow/sql/sql1992.txt)? This wouldn't serve that much nowadays, you would say. Well, we actually tried to do the exercise and we have some interesting conclusions. While we take Elasticsearch as an example for this "side by side", the issues we are addressing also apply to nosql in general. With this unusual exercise, we take the occasion to compare relational databases / sql with Elasticsearch / nosql on all the levels : functionality, semantics, performance and user experience.

Abstract:

In many modern applications the database side is realized using polyglot persistence – store each data format (graphs, documents, etc.) in an appropriate separate database. This approach yields several benefits, databases are optimized for their specific duty, however there are also drawbacks: * keep all databases in sync * queries might require data from several databases * experts needed for all used systems A multi-model database is not restricted to one data format, but can cope with several of them. In this talk i will present how a multi-model database can be used in a polyglot persistence setup and how it will reduce the effort drastically.

Abstract:

Realtime is becoming an essential part of any user experience. Previously, making an app realtime has been difficult to achieve and requires many engineers. Enter Firebase - a realtime NoSQL database that you can access directly from the client. Firebase can function as the complete backend for your web or mobile app, and makes building realtime, collaborative apps easy. In this talk, I'll explain how Firebase works and then we'll live code and deploy an app together.

Abstract:

During this live-coding session, Tugdual will move an old fashion full SQL application (JavaEE) to the new NoSQL world.Using MongoDB, and REST, he will show the benefits of this new architecture: * Easyness * Flexibility * High availability * Scalability; During this presentation, you will learn more about: * Document Oriented Model * JSON * REST * Iterative development; This demonstration is also a good opportunity to see how you can migrate data from a relational database, and the various schema options.