# Presto — Distributed SQL Engine for Interactive Analytics

> Facebook-born distributed SQL engine for running fast, interactive queries against data lakes, warehouses, and federated sources.

## Install

Save as a script file and run:

# Presto — Distributed SQL for Federated, Interactive Analytics

## Quick Use
```bash
# Docker quickstart — a single-node Presto cluster
docker run -p 8080:8080 --name presto prestodb/presto:latest

# Connect with the Presto CLI
presto --server localhost:8080 --catalog hive --schema default

# Example federated query across Hive and MySQL catalogs
SELECT h.event_id, m.customer_name
FROM hive.events.logs h
JOIN mysql.app.customers m ON m.id = h.customer_id
WHERE h.event_date = DATE '2026-04-16';
```

## Introduction
Presto (PrestoDB) is a distributed SQL query engine originally developed at Facebook for running fast, interactive analytical queries against petabyte-scale datasets. Unlike traditional warehouses, Presto separates compute from storage and federates many sources — Hive, Iceberg, MySQL, Postgres, Cassandra, Kafka — through pluggable connectors.

## What Presto Does
- Executes ANSI SQL across heterogeneous data stores in one query.
- Runs interactive, low-latency queries on HDFS/S3 data lakes.
- Federates warehouses and operational databases using 20+ connectors.
- Supports CTAS/INSERT into lakehouse tables (Iceberg, Hudi, Delta via extensions).
- Exposes REST + JDBC/ODBC endpoints for BI tools like Tableau and Superset.

## Architecture Overview
A Presto cluster has one coordinator and many workers. The coordinator parses SQL, plans distributed execution, and splits scans across workers that stream data pages through a pipelined execution model. Connectors adapt external sources to Presto's type system, while the discovery service tracks active workers. Memory is managed with per-node and query-level pools to keep the cluster stable under heavy concurrency.

## Self-Hosting & Configuration
- Packaged as `presto-server` tarball; deploy via Ansible, Kubernetes, or EMR.
- Key config files: `config.properties`, `node.properties`, `jvm.config`, and per-catalog `*.properties`.
- Tune `query.max-memory`, `query.max-memory-per-node`, and `task.concurrency` per workload.
- Use `hive.metastore-uri` to point at a Hive Metastore, AWS Glue, or REST catalog.
- Secure with Kerberos, TLS, LDAP/OAuth2, and system + Ranger authorizers.

## Key Features
- Interactive SQL latency on lake-scale data (seconds to minutes).
- Rich connector ecosystem for federated analytics without ETL.
- Cost-based optimizer with statistics from Hive, Iceberg, and Glue.
- Materialized views and caching (with plugins like Presto cache and Alluxio).
- Strong SQL: window functions, lambdas, geospatial, and approximate aggregates.

## Comparison with Similar Tools
- **Trino** — A community fork of Presto with faster feature iteration; PrestoDB stays aligned with Meta/LinkedIn.
- **Apache Spark SQL** — Batch-centric with streaming; Presto is tuned for interactive latency.
- **Apache Drill** — Schema-on-read file queries; Presto offers richer connectors and optimizer.
- **ClickHouse** — Columnar OLAP DB you own; Presto federates across many existing stores instead.
- **BigQuery / Athena** — Managed cloud analytics; Presto is the open engine you can self-host everywhere.

## FAQ
**Q:** What is the difference between Presto and Trino?
A: Same origin; Trino (formerly PrestoSQL) is an active community fork, while PrestoDB evolves at Meta, LinkedIn, and the Linux Foundation's Presto Foundation.

**Q:** Does Presto store data?
A: No — it is a query engine only. Storage lives in S3, HDFS, Hive, Iceberg, RDBMS, and other catalogs.

**Q:** How many nodes do I need?
A: A small cluster of 3–5 workers handles GB-scale analytics; large deployments run hundreds of workers.

**Q:** What clients can connect?
A: JDBC, ODBC, Python (`presto-python-client`), Node.js, Go drivers, and the `presto` CLI.

## Sources
- https://github.com/prestodb/presto
- https://prestodb.io/docs/current

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Source: https://tokrepo.com/en/workflows/5f0c50a5-3931-11f1-9bc6-00163e2b0d79
Author: Script Depot