Announcement
Presto - The Distributed SQL Query Engine for Big Data
Presto is an open-source distributed SQL query engine designed for running interactive analytical queries against various data sources, including Hadoop, S3, Cassandra, MySQL, and more, without moving data.
Project Introduction
Summary
Presto is a high-performance, distributed SQL query engine developed to enable fast, interactive analytics on large datasets from diverse sources. It allows organizations to query their existing data infrastructure using standard SQL.
Problem Solved
Presto addresses the challenge of querying vast, distributed datasets residing in disparate systems (like data lakes, data warehouses, and transactional databases) efficiently, overcoming limitations of traditional data processing frameworks for interactive analysis.
Core Features
Distributed Architecture
Scales to petabytes of data and thousands of users by distributing query execution across a cluster of machines.
Pluggable Connectors
Provides connectors to query data from various sources like HDFS, AWS S3, Cassandra, MySQL, PostgreSQL, and more, enabling data federation.
ANSI SQL Compliance
Supports standard ANSI SQL syntax, making it easy for users familiar with relational databases to start querying big data.
In-Memory Processing
Optimizes query execution speed by performing processing in memory whenever possible.
Tech Stack
使用场景
Presto is ideally suited for scenarios requiring fast, low-latency data access and analysis across distributed data stores. Common use cases include:
场景一：交互式数据分析
Details
数据分析师和数据科学家可以使用Presto对大型数据集进行实时、即席查询，进行数据探索和商业智能分析。
User Value
显著加快数据分析周期，从数小时或数天缩短至数秒或数分钟，提高分析效率和决策速度。
场景二：数据湖查询
Details
直接查询存储在数据湖（如S3、HDFS）中的原始或处理过的数据，无需ETL到数据仓库。
User Value
简化数据架构，降低数据移动和存储成本，提高对原始数据的直接访问能力。
场景三：数据联邦与虚拟化
Details
通过Presto的连接器同时查询来自不同数据库、数据仓库和数据湖的数据源。
User Value
提供统一的数据访问层，用户可以使用单一工具查询分散在不同位置的数据，实现数据联邦和简化视图。
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