The Distributed Data Show

We talk with Dikang Gu about Instagram’s experience migrating from Apache Cassandra 2.2 to 3.0 and using Rocks DB as a pluggable storage engine for Cassandra.

We talk with Dr. Denise Gosnell, graph consultant at DataStax about creative applications of graph technology, TOTAL DOMINATION, and some surprising use cases.

DataStax CTO Jonathan Ellis compares the tradeoffs, strengths, and weaknesses of Apache Cassandra vs. Amazon’s DynamoDB, Microsoft’s Azure Cosmos DB, and Google’s Cloud Spanner.

Patrick McFadin catches up with Holden Karau of Google to learn about new features of Spark 2.3, including Vectorized UDFs, Microbatch improvements, and Kubernetes support. Along the way, they explore whether API stability is an indicator that it’s time to make a career move. 

DuyHai Doan leads a discussion with Patrick McFadin and Jeff Carpenter on whether blockchain is a database, how blockchains and distributed databases complement each other,  and what we can learn about distributed systems by looking at blockchain technology. 

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.