It has been a while since you left the easy days of batch processing behind: the lazy ETL jobs that had all night to run, the relaxed SLAs that let you take lunches like Don Draper, the languid bankers’ hours: the salad days of your data processing career. Those days are over now, and producing real-time results on streaming data is the new order of the day. Two seconds is the new overnight.
Apache Kafka is a de facto standard streaming data processing platform, being widely deployed as a messaging system, and having a robust data integration framework (Kafka Connect) and stream processing API (Kafka Streams) to meet the needs that common attend real-time message processing.
On top of that, Kafka now offers KSQL, a declarative, SQL-like stream processing language. What once took some moderately sophisticated Java code can now be done at the command line with a familiar and eminently approachable syntax. Come to this talk for an overview of KSQL with live coding on live streaming data.
Tim is a teacher, author, and technology leader with Confluent, where he serves as the Senior Director of Developer Experience.
At Seenit, we enable our clients to power their digital transformation programmes with the power of video by engaging with their communities to tell the stories that matter most. Seenit uses Couchbase’s powerful N1QL and Full Text Search engines to allow content producers to create the most effective and trustworthy content.
Dave is the Chief Technology Officer of Seenit, a London-based video collaboration platform, and a Couchbase Developer Expert. He has been using Couchbase since the 2.0 era, and he and his team are putting it to use at Seenit to build a video intelligence data mining tool and search engine.