Welcome to issue 247 of NoSQL Weekly.

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Articles, Tutorials and Talks

Big Data and NoSQL for Oracle DBAs: What You Need to Know
Big data and NoSQL allows us to scale to volumes that are not possible with traditional relational database systems at lower cost and in less time. The cost and size of storage has kept pace with our data requirements; however, transfer rates have not. Big data and NoSQL are architecture to solve this problem by bringing the compute to the data and not the other way around. During this presentation, you will learn what Big Data toolsets are and how they are different from relational database systems, including the Oracle In-Memory Database Option.

Understanding Repairs in Apache Cassandra
Cassandra was designed as a truly high-available datastore. Being able to always serve reads and writes will also imply situations in which data will diverge across nodes in a cluster. Executing repairs will allow us to synchronize effected data again to restore a consistent replica set. As availability and consistency are both important, executing regular repairs becomes a basic requirement. Understanding how repairs work can be complex, but it's also fundamental for successfully operating large Cassandra clusters in production.

Mapping a Value Stream in Neo4j
The canonical use cases of a graph database such as Neo4j are social networks. In logistics and manufacturing networks also arise naturally. In particular, supply chains and value streams spring to mind. They may not be as large as Facebook's social graph of all its users, but seeing them for the beasts they truly are can be beneficial. In this post I therefore want to talk about how you can model a value stream in Neo4j and how you can extract valuable information from it.

Reconstructing Payloads With Lua
Redis has provided Lua for scripting since version 2.6.0. Typically it is used for transactional semantics and more advanced queuing behavior. Today we are going to look at a data driven use-case for executing Lua scripts in Redis.

Couchbase without Compromise
Joyent CTO, Bryan Cantrill, sits down with Couchbase's Traun Leyden to understand why the team at Couchbase is so excited about the Triton elastic container service and how you can easily use Triton to spin up a Couchbase cluster within minutes.

Generating graphs for Graph Commons with Neo4j
This post demonstrates how to extract data from a Neo4j database and import it into Graph Commons. It also provides some tips for fine-tuning and sharing your graph. Even though this demonstration is based on Neo4j, you should be able to apply the same techniques to prepare graphs for Graph Commons with your own favorite tool.

Push Databases with RethinkDB CEO Slava Akhmechet

The Gremlin Graph Traversal Machine and Language

Spring Data Couchbase: A New Generation (2.0 Preview)

Clustering a Node.js application with Mongo, Docker and Rancher


MongoDB for Java Developers
This book is for Java developers and architects who want to learn how to develop Java applications using the most popular NoSQL solution and the use cases of it.

Interesting Projects, Tools and Libraries

Rb, the redis blaster, is a library that implements sharding for redis. It implements a custom routing system on top of python redis that allows you to automatically target different servers without having to manually route requests to the individual nodes.

Stubbed Cassandra runs as a separate process that your application will believe is a real Cassandra node. It does this by implementing the server side of the binary protocol. It allows you to create scenarios like read time outs, write time outs and unavailable exceptions so you can test your application.

A ephemeral CouchDB-like database.

Upcoming Events and Webinars

Webinar: MongoDB Schema Design and Performance Implications
One of the challenges that comes with moving to MongoDB is figuring how to best model your data. Learn how different MongoDB schemas may result in wide differences in database size, query performance, and required hardware.

Webinar: Apache Spark Solution for Rank Product
The "rank product" is a statistical technique, used for detecting differentially regulated genes in replicated microarray experiments. The technique has achieved widespread acceptance and is now used more broadly, in such diverse fields as RNAi analysis, proteomics, and machine learning. The "rank product" technique may be used in ranking users (in social networks) and items (such as Amazon.com). Given large set of genes, users, or items, in this webcast I will present two distinct Spark solutions: (using groupByKey() and combineByKey()) for solving the "rank product".

Graph Analytics Meetup @ Facebook - San Francisco, CA
Join us for multiple talks on graph analytics and graph storage, and meet other members of the graphdb community. The talks will include recent advances from the Facebook team in the area of graph processing systems but also work on graph management technologies from external speakers.

Neo4j Full Stack Applications - Lessons and Disasters from the field. - London, United Kingdom
In this talk Matt Wright from Stitched will share his team's successes and failures in building Search algorithms, Social Networking applications, recommendation engines, graph visualisations and Java Unmanaged Extensions in neo4j. He'll also point out the potential pitfalls that lie in wait and how to avoid them.

Intro to C* + 2 Great Use Cases - London, United Kingdom
We have a quick 20 min intro to Cassandra for those who have joined the group recently or who want a quick refresh! And we also have 2 great guest speakers with Saket telling us how they use C*+Spark at BGCH and Carlos who is going to delight us with the talk he will present at Santa Clara Cassandra Summit in September!

MongoDB 3.0 Deep Dive + Riak - Seattle, WA

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