Distributed Data Show

David Gilardi talks with Kiyu Gabriel and Darla Baker about the DataStax Managed Cloud and gets some details on the advantages of using a managed service for your distributed database.

Kat Erickson announces the availability of official Docker images of DataStax Enterprise and why you should use them.

DuyHai Doan shares his advice on debugging graph traversals using the Gremlin query language, including how to identify and fix performance bottlenecks and his thoughts on the “supernode” challenge.

David Gilardi talks with Stephen Mallette about domain specific languages for graph databases in Java, when you should use a DSL, and some of the implementation details you’ll want to know to succeed.

Patrick McFadin, Luke Tillman and Jeff Carpenter sit around the campfire telling Cassandra data modeling horror stories, dad jokes and the occasional spooky noise.

Wei Deng talks about the challenges involved in securing distributed databases, the latest security features in DataStax Enterprise, and recommended techniques to help you and your company stay out of the headlines.

DuyHai Doan takes us inside of Apache Kudu, a data store designed to support fast access for analytics in the Hadoop ecosystem. We compare Kudu’s architecture with Apache Cassandra and discuss why effective design patterns for distributed systems show up again and again.

Denise Gosnell talks about working with Graph and why not every problem is a graph problem.

DuyHai Doan talks about secondary indexes in Apache Cassandra, including how they work, how they are different than indexes in relational databases, the various implementations available, and when to use them.

Luke Tillman talks about his dogfooding project for DataStax Academy, challenges of developing microservice applications, and how distributed tracing throughout the stack can help.

Patrick McFadin and Jeff Carpenter talk about the latest trends in data development and share their thoughts on which trends you should be following and what tech it’s time to start learning, and why Jeff looks familiar.

DSE Analytics badass Russ Spitzer brings us up to speed on the latest developments in Apache Spark and the implications for DataStax Enterprise Analytics.

Tanya Gallagher explains why you need a learning path for Apache Cassandra and DataStax Enterprise and gives us an inside look at how the DataStax Curriculum Engineering team stays up to speed as they maintain content like our free online courses at DataStax Academy and live, instructor-led training.

DuyHai Doan (@doanduyhai) shares about his experiences supporting DataStax customers in Europe, including some of the most common misunderstandings he sees regarding configuring Apache Cassandra and DataStax Enterprise clusters for high availability.

Bob Briody (@bobbriody) explains the origins and capabilities of DataStax Studio, a powerful developer enablement tool for querying and visualizing both graph (Gremlin) and CQL data. Join us to learn about the most underrated feature of Studio and some hints on new features the Studio team has in the works.