Kora Engine, Data Quality Rules y mucho más en nuestra nueva versión del 2T'23 | Regístrese para la demostración
When things get a little bit cheaper, we buy a little bit more of them. When things get cheaper by several orders of magnitude, you don't just see changes in the margins, but fundamental transformations in entire ecosystems. Apache Pinot is a driver of this kind of transformation in the world of real-time analytics.
Pinot is a real-time, distributed, user-facing analytics database. The rich set of indexing strategies makes it a perfect fit for running highly concurrent queries on multi-dimensional data, often with millisecond latency. It has out-of-the box integration with Apache Kafka, S3, Presto, HDFS, and more. And it's so much faster on typical analytics workloads that it is not just a marginally better data warehouse, but the cornerstone of the next revolution in analytics: systems that expose data not just to internal decision makers, but to customers using the system itself. Pinot helps expand the definition of a ""decision-maker"" not just down the org chart, but out of the organization to everyone who uses the system.
In this talk, you'll learn how Pinot is put together and why it performs the way it does. You'll leave knowing its architecture, how to query it, and why it's a critical infrastructure component in the modern data stack, particularly in combination with architecture based on Kafka. This is a technology you're likely to need soon, so come to this talk for a jumpstart.