Xavier Amatriain discusses how Netflix uses specialized roles, including that of the Data Scientist and Machine Learning Engineer, to deliver valuable data at the right time to Netflix' customer base through a mixture of offline, online, and nearline data processes. Xavier also discusses what it takes to become a Machine Learning Engineer and how to gain real experience in the field.
Eva Andreasson explains the various Hadoop technologies and how they interact, real-time queries with Impala, the Hadoop ecosystem including Hue, Oozie, YARN, and much more.
Sadek Drobi explains the benefits of functional programming for the web. Also: improving CMS by separating content from representation and how prismic.io implements ideas from functional DBs and Git.
Etsy's approach to big data has been to give the entire organization visibility to different sources of data generated by their product as well as access to the experts who know how to use it. Nell Thomas explains her role at Etsy and how Etsy's view of big data has shaped its product's evolution.
Emil Eifrem looks back at the history of Neo4j, an open-source, NoSQL graph database supported by Neo Technology. He describes some real world applications of graphs, domain modelling with graphs, and compares the performance of graph and relational databases. He also examines how Neo4j differs from other NoSQL and graph databases in the market and describes various Neo4j licensing options.
Big Data means more than just the size of a dataset. Pavlo Baron explains different ways of applying Big Data concepts in various situations: from analytics, to delivering content, to medical applications. His larger vision for Big Data ranges from specialized Data Scientists, to learning Decision Support Systems, to helping mankind itself.
Ian Robinson discusses Neo4J's design choices for data storage and retrieval, CRUD operations, transactions, graph traversal and searches and HA deployment strategies. He also shares his thoughts on hypermedia controls and the concept of consumer driven contracts for continuous evolution of services.
In this interview, Michael Hunger talks about the evolution of persistence technologies over the last decade, the emergence of NoSQL databases, and looks at where graph databases fit in. He describes the goals behind the Spring Data Neo4j project, it's latest developments, and examines Cypher, a humane and declarative query language for graphs.
Rich Hickey explains the basics of Datomic, its approach to transactions and query, Datalog, CAP, ACID and BASE, and much more.
Erik Meijer explains the various aspects needed to categorise data stores, how reactive programming fits in with databases, the return to data transformation, denotational semantics, and much more.
Debasish Ghosh talks about the advantages of functional programming and how its abstractions help to reason about code, Monads, DSLs, NoSQL and MongoDB, and much more.
CONTENT IN THIS BOX PROVIDED BY OUR SPONSOR
- 10 Things Developers Should Know about Couchbase
- When one is better than two: Collapsing data management layers for scalability and simplicity
- Couchbase NoSQL @ Tunewiki : A billion documents and counting
- The Essential Couchbase APIs Cheat Sheet
- Why MySQL 5.6 is no real threat to NoSQL
- How to Move from MySQL to Couchbase Server 2.0: Part 1
- Making Sense of NoSQL
- Couchbase in Action – Real world app demo
- Making the Shift from Relational to NoSQL