The Distributed Data Show

We talk with Nick Panahi, Product Manager for DSE Search, about the distinction between secondary indexes and search indexes, the challenges of distributed search engines, and future directions for DSE Search.

The evangelist team shares some its internal discussions and debates about the intersection of microservice architecture and the data tier.

We talk with Kat Erickson about the popularity of orchestration frameworks like Kubernetes and the pros and cons of using orchestration for deployment of distributed databases. 

The DataStax Evangelist team offers their predictions on the big technology trends to look for in 2018, including microservices and service meshes, containers and orchestration, and the emergence of higher level managed services for machine learning and AI applications. 

DuyHai Doan and Patrick McFadin explain the primary two ways of distributing data used in computer science: hash-based partitioning and range-based partitioning, and the implications of each of these on operations (hint: rebalancing!). 

Patrick McFadin talks with David Gilardi about the new recommendation engine recently added to the KillrVideo reference application using DSE Graph and Java DSL’s (Domain Specific Language).

Luke Tillman and DuyHai Doan talk about why pre-aggregation is difficult on an eventually consistent database like Apache Cassandra, and debate whether the storage engine in Cassandra should be made pluggable.

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.