Understanding Presto UI: A Deep Dive into the Web Interface Architecture 

    Presto UI is a modern, React-based web interface that provides real-time monitoring, query management, and cluster administration capabilities for the Presto distributed SQL query engine. Whether you’re a database administrator, data engineer, or developer, Presto UI offers intuitive tools to visualize query execution, monitor cluster health, and interact with the Presto coordinator. Key Benefits of…

    Seamless Integration: Connecting PrestoDB to SingleStore for High-Performance Analytics

    In today’s data-driven landscape, organization’s are constantly seeking ways to analyze massive datasets quickly and efficiently. PrestoDB, a powerful open-source SQL query engine, and SingleStore, a distributed SQL database, are two technologies that, when combined, offer unparalleled capabilities for high-performance data querying and distributed analytics. This guide provides a hands-on, step-by-step tutorial on how to…

    Presto Takes a Leap: Upgrading to Java 17 for Enhanced Performance and Security

    We’re excited to announce that the core Presto engine is migrating to Java 17. This upgrade reinforces our commitment to providing a robust, high-performance, and secure SQL query engine. This change allows Presto to leverage Java 17’s improvements, bringing enhancements in performance, stability, and security, and laying a strong foundation for future upgrades. Why Java…

    Prestissimo Extension for AI Training Data Normalization at Meta: A Deep Dive for Developers (Lightning Talk)

    At PrestoCon Day 2025, Meta’s Presto team recently unveiled the Prestissimo extension, a powerful enhancement designed to optimize AI training data normalization. This article explores the technical underpinnings and developer-centric features of this extension, providing a comprehensive understanding of how it supports large-scale AI workloads at Meta.  Understanding AI Training Data Storage at Meta At…

    Presto C++ Unleashed: Dynamically Load Unfenced UDFs, End Rebuilds, and Boost Performance

    Dynamic loading in Presto C++ is revolutionizing how developers build and deploy user-defined functions (UDFs). At PrestoCon Day 2025 , Soumya Duriseti explained how Presto C++ now supports dynamic loading of unfenced UDFs, eliminating the need for time-consuming static builds and making it easier than ever to add custom logic without rebuilding the entire binary….

    Building Connectors in Presto C++: Deep Dive into the TPCDS Connector (Lightning Talk) 

    At PrestoCon Day 2025, engineers from IBM presented a deep dive into how connectors in Presto C++ extend the engine’s modular capabilities, focusing on the newly implemented TPCDS benchmark connector. Connectors are central to Presto’s architecture, enabling the query engine to communicate seamlessly with external systems such as databases, file formats, or benchmark data generators….

    Presto’s Intelligent Future: Leveraging RAG and LLM’s for Smarter Query Execution 

    At PrestoCon Day 2025, Satej Sahu (Principal Data Engineer at Zalando SE) introduced the Self-Healing Query Connector for Presto, an AI-powered upgrade designed to make query troubleshooting faster, smarter, and more reliable. By combining Large Language Models with live query data, including logs, explain plans, and schema details it delivers accurate, context-aware solutions that improve…

    Revolutionizing Presto C++: Unleashing Native Power with the Sidecar 

    At PrestoCon Day 2025, we unveiled the Presto Sidecar, a powerful enhancement for Presto C++ (Velox) clusters that transforms how coordinators interact with native workers. This innovation removes long-standing blind spots in query planning by giving the coordinator real-time visibility into native worker capabilities – such as supported functions, data types, session properties, and plan…

    Unlocking Petabyte-Scale Performance: Uber’s Journey with Presto for Distributed Cache using Alluxio 

    At PrestoCon Day 2025, Uber presented their innovative solution for optimizing petabyte-scale data analytics by deploying a distributed cache using Alluxio for Presto. Their journey was driven by significant challenges during a massive cloud migration, including read slowness and overwhelming HDFS clusters on-premises, and later high GCS egress costs and file access charges in the…

    Unleashing Interactivity: Inside Meta’s Presto-Powered Data Warehouse Innovation

    At this year’s PrestoCon Day, Meta had an awesome session to share the latest on what they’re doing with Presto. As you probably know, Meta has one of the largest data Lakehouse’s in the world and Presto is a critical piece of that data platform. It plays a critical role in serving vast and diverse…

    Setting Up Presto with Apache Superset: Hands-On Guide

    PrestoDB, an open-source distributed SQL query engine, allows you to query data from multiple disparate sources. When combined with Apache Superset, an open-source data visualization and exploration platform, it forms a powerful and flexible analytics solution. This guide provides a step-by-step approach to deploying these components within a Dockerized environment, simplifying setup and management. Pre-Requisites:…

    Build Your Open Data Lakehouse: A Step-by-Step ETL Guide with MySQL, OLake, and PrestoDB

    This tutorial provides a comprehensive guide to building an Open Data Lakehouse from scratch, a modern and flexible data architecture solution. Open Data Lakehouses offer a powerful and scalable method for storing, managing, and querying both structured and semi-structured data, leveraging a suite of robust open-source tools for enhanced control and flexibility. Pre-Requisites: Before commencing…

    Leading by Contribution: IBM’s Ongoing Investment in Open-Source Presto 

    Note: This is a cross-post from https://community.ibm.com/community/user/blogs/ali-leclerc/2025/07/15/ibms-ongoing-investment-in-presto At IBM, we believe open source is the engine of innovation. Presto, as a fast and flexible SQL engine for interactive analytics, continues to evolve rapidly thanks to community contributions. Over the past year, IBM engineers have focused on driving Presto forward across security, performance, native execution, and…

    Setting Up Presto: A Step by Step Installation Guide to Run SQL Queries 🚀

    In this guide, I’ll walk you through installing Presto and show how to run queries with ease. Pre-Requisites 🎯Before getting started, ensure that the following are installed: Now, let’s see the Step by Step Process to Install Presto. Step – 1: Installing Presto Server 📥 📌 wget – Fetches the specified URL and save the file locally…

    How Twilio Scales Presto with Odin: A New Query Gateway

    One of my favorite parts of working with the Presto community is seeing how different companies push the project forward in creative ways. Recently, Aakash Pradeep from Twilio shared a great example of this with their development of Odin, a new modular query gateway they built to help scale Presto usage across their organization.  I…

    Fueling Presto’s Momentum and IBM’s Growing Role in the Open-Source SQL Engine

    I’ve now been a part of IBM for 2 years and I’m pretty encouraged with the work this team has put into open-source Presto. So, I wanted to take some time to share in a blog what we’ve been up to for the last 2 years and the growth we’ve seen collectively in the community…

    Safeguarding Presto C++ Memory Usage with LinuxMemoryChecker

    Problem  Running the Presto C++ worker stably in a production environment relies on proper configuration that maximizes stability without sacrificing performance. Presto C++ designed a LinuxMemoryChecker to achieve this goal.   The evaluation engine used in Presto C++ is Velox. Velox, the evaluation engine used in Presto C++, implements a MemoryManager that provides several advanced features…

    Improving Schema Management in Presto: Passing Catalog Names to the Metastore

    Managing schemas in Presto just got a lot smarter. Thanks to a new enhancement, Presto can now pass catalog names directly to the metastore, enabling better logical organization, filtering, and schema isolation across multiple catalogs. This improvement significantly enhances the experience for users working with Hive, Hudi, Delta, and Iceberg catalogs.  🔍 The Problem Before …