Fast Path to Streaming Data Analysis

Rill Data assists companies in overcoming the challenges of analyzing streaming data by providing a platform that combines efficient data modeling and high-performance processing, enabling real-time sub-second online analytical processing (OLAP). The platform integrates with BI tools like Tableau and Looker, and when data enrichment is necessary, it pairs well with ksqlDB and Apache Druid, facilitating the transformation of streaming data into actionable insights. An illustrative exercise using OpenSky Network aircraft telemetry data demonstrates the ease of setting up data streams through Rill, enriching them with ksqlDB user-defined functions, and capturing data for OLAP queries using Apache Druid. Visualization tools such as Apache Superset are used to display the enriched data, providing dynamic, real-time insights into aircraft movements. The text also highlights the importance of preventing data duplication and ensuring exactly-once semantics within streaming applications, with Rill managing Apache Druid and real-time Kafka infrastructure for clients. The open-source tools and scripts supporting these processes are available in a GitHub repository, offering a comprehensive demonstration and exploration of the technologies involved.