Estimated reading time: 10 minutes

Multiple data science personas participate in the daily operations of data logistics and intelligent business applications. Management and employees need to understand the big picture of data science to maximize collaboration efforts for these operations. This article will highlight the specialized roles and skillsets needed for the different data science tasks and the best tools to empower data-driven teams. You will come away from this article with a better understanding of how to support your own data science teams, and it is valuable for both managers..

Estimated reading time: 3 minutes

Today is a marvelous day for the ArangoDB project and the community behind it.

A couple of minutes ago, the 10,000th stargazer joined the project on GitHub, and we want to send a really big “Thank You!” to each and everyone of you for showing your support.

Here is a slideshare and recording of my talk about multi-model databases, presented in Santa Clara earlier this month.

Abstract: Recently a new breed of “multi-model” databases has emerged. They are a document store, a graph database and a key/value store combined in one program. Therefore they are able to cover a lot of use cases which otherwise would need multiple different database systems. This approach promises a boost to the idea of “polyglot persistence“, which has become very popular in recent years although it creates some friction in the form of data conversion and synchronisation..

Max wrote an inspiring article about graphs in data modeling on Medium, packed with his own thoughts – “to sort out some things in my brain” (Max).

He asks and answers the question: Are graphs and graph databases useful in data modeling, and if so, for what and under which circumstances?

In his article, he goes all the way down from the theoretical approach of what is a graph? towards storing a graph in different storage models (RDBMS, document store and graph databases) to querying a graph and finally to his personal conclusion.

In Next gen NoSQL: The demise of eventual consistency a recent post on Gigaom FoundationDB founder Dave Rosenthal proclaims the demise of eventual consistency. He argues that Google Spanner “demonstrates the falsity of a trade-off between strong consistency and high availability”. In this article I show that Google Spanner does not disprove CAP, but rather chooses one of many possible compromises between total consistency and total availability. For organizations with a less potent infrastructure than Google other compromises might be more suitable, and therefore eventual consistency is still..