Sort by:

Spark and Streaming with Matei Zaharia

Apache Spark is a system for processing large data sets in parallel. The core abstraction of Spark is the resilient distributed dataset (RDD), a working set of data that sits in memory

Demystifying Stream Processing with Neha Narkhede

“Systems are giving up correctness for latency, and I’m arguing that stream processing systems have to be designed to allow the user to pick the tradeoffs that the application
demystifying stream processing with kafka

Stream Processing with Satish Mittal

“We still need to see in the long run how much of community and industry adoption is there. Because at the end of the day, these are the single two most important things which define
stream processing frameworks

Transactions and Analytics with VoltDB’s Ryan Betts

Streaming pipelines and in-memory analytics are difficult to support with old database systems. VoltDB provides streaming analytics with transactions.     Questions How does

Streaming SQL with PipelineDB CEO Derek Nelson

PipelineDB is a streaming SQL database. Derek Nelson is the CEO of PipelineDB. Questions What are continuous views? Why is PipelineDB a good fit for the Kafka+Storm+HBase-type