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.
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.
In this interview recorded at QCon New York 2012 Conference, Robert Greene from Versant Corporation discusses Versant's NoSQL database and their JPA 2.0 compliant Java NoSQL solution. He also talked about transparency of data access across the physical nodes when using NoSQL databases.
Ken Little talks about scaling Tumblr to keep up with their blogging users: scaling the data model, sharding, their PHP frontend and the Scala backend, and much more.
In this interview recorded at QCon NY 2012 Conference, Jim Webber from Neo Technology discusses the Graph database ecosystem, graph use cases, and tools for developing applications using Neo4j graph database.
Eric Evans shares his view on how the last trends in technology, such as NoSQL, functional languages, thick browser-based client, JSON and others, make him rethink some of the DDD concepts.
Rich Hickey explains how immutability enables Datomic's features and facilitates programming (not just in functional languages). Also: Datomic and other NoSQL stores, Clojure Reducers and much more.
Rich Hickey and Justin Sheehy talk about scalability and transactionability of datastores. They explain tradeoffs for achieving read and/or write scalability on top of Datomic and Riak.
In this interview recorded at QCon New York 2012 Conference, VMWare's Mike Stolz talks about the design patterns that help with processing and analyzing the unstructured data. He also explains the patterns for combining Fast Data with Big Data in finance applications as well as the role of in-memory databases in NoSQL database space.
In this interview at QCon London, LinkedIn’s Sid Anand discusses the problems they face when serving high-traffic, high-volume data. Sid explains how they’re moving some use cases from Oracle to gain headroom, and lifts the hood on their open source search and data replication projects, including Kafka, Voldemort, Espresso and Databus.
Rich Hickey explains the ideas behind the Datomic database: why Datalog is used as the query language, the functional programming concepts at its core, the role of time in the DB and much more.