Videos Archive - PrestoDB

PrestoDB in HPE Ezmeral Unified Analytics – Milind Bhandarkar, HPE

HPE Ezmeral Unified Analytics is an end-to-end data & AI/ML platform that consists of several popular open-source frameworks for data engineering, data analytics, data science, & ML engineering in a well-integrated packaging. These open-source frameworks include Apache Spark, Apache Airflow, Apache Superset, PrestoDB, MLFlow, Kubeflow, and Feast. This platform is built atop Kubernetes and provides built in security. In this talk we will focus on the role of PrestoDB in Unified Analytics as a fast SQL query engine, and also as a secure data access layer. We will discuss some of our value-additions to PrestoDB, such as a distributed memory-centric columnar caching layer that provides both explicit and transparent caching for dataset fragments, often leading to 3x to 4x query performance. We will conclude by proposing to make caching pluggable in PrestoDB and discussing future directions.

How Carbon uses PrestoDB in the Cloud with Ahana to Power its Real-time Customer Dashboards

Carbon is a real-time revenue management platform that consolidates revenue and audience analytics, data management, and yield operations into a single solution. Real-time analytics is super critical – their customers rely on real-time data to make revenue decisions. After facing issues around performance, visibility & ease of use, and serverless pricing model with AWS Athena, the team moved to a managed service for PrestoDB in the cloud – Ahana Cloud – to power their customer-facing dashboards. In this session, Jordan will discuss some of the reasons the team moved from AWS Athena to a managed PrestoDB on Intel-optimized AWS instances. He will also dive into their current architecture that includes an Ahana-managed Hive Metastore along with Apache ORC file format and an S3-based data lake. Last, he’ll share some performance benchmarks and talk about what’s next for PrestoDB at Carbon.