Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

Schedule: Real-time applications sessions

2:05pm2:45pm Wednesday, September 27, 2017
Location: 1A 23/24 Level: Intermediate
Secondary topics:  Streaming
Todd Lipcon (Cloudera)
Average rating: *****
(5.00, 3 ratings)
To date, mutable big data storage has primarily been the domain of nonrelational (NoSQL) systems such as Apache HBase. However, demand for real-time analytic architectures has led big data back to a familiar friend: relationally structured data storage systems. Todd Lipcon explores the advantages of relational storage and reviews new developments, including Google Cloud Spanner and Apache Kudu. Read more.
1:15pm1:55pm Thursday, September 28, 2017
Location: 1E 09 Level: Beginner
Secondary topics:  Architecture, Streaming
Matteo Merli (Streamlio), Sijie Guo (ASF)
Average rating: *****
(5.00, 2 ratings)
Modern enterprises produce data at increasingly high volume and velocity. To process data in real time, new types of storage systems have been designed, implemented, and deployed. Matteo Merli and Sijie Guo offer an overview of Apache DistributedLog and Pulsar, real-time storage systems built using Apache BookKeeper and used heavily in production. Read more.
4:35pm5:15pm Thursday, September 28, 2017
Location: 1A 06/07 Level: Intermediate
Secondary topics:  IoT, Streaming
Arun Kejariwal (Independent), Francois Orsini (MZ), Dhruv Choudhary (MZ)
Average rating: *****
(5.00, 3 ratings)
Services such as YouTube, Netflix, and Spotify popularized streaming in different industry segments, but these services do not center around live data—best exemplified by sensor data—which will be increasingly important in the future. Arun Kejariwal, Francois Orsini, and Dhruv Choudhary demonstrate how to leverage Satori to collect, discover, and react to live data feeds at ultralow latencies. Read more.