DuckDB in the Cloud: A Simple, Powerful SQL Engine for Your Lakehouse
UB2.252A (Lameere) | Day 1 | 13:15 - 13:20 | Speakers: Gábor Szárnyas, Guillermo Sanchez, Tom Ebergen
Abstract
DuckDB has traditionally been seen as a last-mile analytics powerhouse, the fastest way to run a SQL query on your laptop. But DuckDB offers more than just fast SQL, of course; it supports full database semantics and ACID transactions, behaving like a fully fledged, in-process OLAP database. The in-process component has sometimes been viewed as a limitation when considering DuckDB as a data warehouse.
However, DuckDB now supports reading and writing to most Open Table Formats (OTFs), including Iceberg, Delta, and DuckLake. This capability puts DuckDB in a very different position: it allows DuckDB to act as a SQL engine in the cloud (or on your local machine) and run queries against any OTF stored in remote cloud storage. DuckDB can now be the all-mighty, single-node query engine that powers your data analytics use cases.
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Speakers
Gábor Szárnyas is a database researcher at DuckDB Labs. He obtained his PhD in software engineering and was a post-doctoral researcher at CWI Amsterdam, the birthplace of DuckDB. He is also a core contributor and board member of the LDBC non-profit organization (ldbc.org) that defines benchmarks for graph data management systems.
Guillermo has been working in the data space as a Data Engineer and Architect for over 7 years. His experience with Big Data platforms like Snowflake and Databricks (and some others) convinced him that an alternative, simpler approach may be all we need to make good analytics work. That's why he decided to join DuckDB Labs to work in Product and Developer Relations.
Tom Ebergen is a software engineer at DuckDBLabs responsible for maintaining the DuckDB-Iceberg extension. He also makes frequent contributions to the DuckLake extension, DuckDB-httpfs extension and the db-benchmark hosted by DuckDB Labs.
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