It stores data in a compressed columnar format, which provides the best performance for large-scale aggregations. Fast Aggregation and Excellent SQL Support, the Key to AnalyticsĭuckDB is designed as an analytics database from the bottoms up – aiming to squeeze every ounce of performance while also allowing you to perform complex analytics queries using standardized SQL.Īs an analytics database, DuckDB is optimized for read operations and can also perform updates in a transactional ACID-compliant fashion. Additionally, DuckDB is available in Python, R, Javan, node.JS, Julia, C/C++, and WASM. Print(duckdb.query( "SELECT sum(a) FROM mydf ").fetchall())ĭuckDB enables users to connect to powerful BI tools like Tableau, Looker, or Superset with standard ODBC or JDBC drivers. DuckDB can even treat pandas dataframes as DuckDB tables and query them directly. ![]() While pandas enables rich and powerful data science transformations, DuckDB dramatically accelerates analytical workloads, with the added benefit of using a standard SQL interface. These are all valid SQL statements in DuckDB: SELECT AVG(trip_distance) FROM 's3://yellow_tripdata_20*.parquet' SELECT * FROM '~/local/files/file.parquet' SELECT * FROM dataframeĭo you have Arrow tables, PostgreSQL databases or SQLite databases? DuckDB can directly query those too no import required! Use with Popular Tools and FrameworksĭuckDB rose in prominence thanks to its ease of use in Python alongside pandas, a hugely popular library for data science. With DuckDB, you’re at most one or two commands away from querying data where it lies, whether it’s on your local hard drive, in the cloud, or in another database. DuckDB challenges the current status quo that needlessly complicates access to these diverse data sources. Simplified Data AccessĪnalysts often tell us that they wish to analyze data that lives in disparate places - CSV files on their laptops, Parquet files on S3, dataframes in their Python notebooks, and even tables in relational databases. DuckDB is universally useful for data scientists, analysts, data engineers, and application developers. You can use DuckDB in Python notebooks, R scripts, Javascript data apps, or Java backends. Thus you can run DuckDB on your laptop, in the browser, on a cloud VM, in a cloud function, and even in a CDN edge point-of-presence. DuckDB is portable and modular, with no external dependencies. Thanks to DuckDB, practically any CPU in the world can now be mobilized to perform powerful analytics. Additionally, DuckDB can analyze data wherever it lives, be it on your laptop or in the cloud.ĭuckDB comes with a command-line interface for rapid prototyping, and you can try DuckDB right now using the hosted DuckDB shell. DuckDB can be thought of as “SQLite for analytics” - you can embed it in virtually any codebase and run it in virtually any environment with minimal complexity.Īs an in-process database, DuckDB is a storage and compute engine that enables developers, data scientists and data analysts to power their code with extremely fast analyses using plain SQL. First, What is DuckDB?ĭuckDB is an open source in-process SQL OLAP database management system. When we founded MotherDuck we recognized that DuckDB might just be the next major game changer thanks to its ease of use, portability, lightning-fast performance, and a rapid pace of community-driven innovation. ![]() For example, the modern cloud data warehouse arose a decade ago on a foundation of powerful cloud storage, compute, and networking. Whereas a basic support has limited features available.įor more information on the support types, refer to the Other databases topic.Industries transform on the back of momentous technological change. All the inspections, quick-fixes, and other code assistance features are also available. ![]() DataGrip provides a complete support for the following database vendors:Ĭomplete support of a database vendor includes such features as enhanced code completion and better retrieval of database objects (introspection). Select a database that you want to connect to.
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