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Dbt enables analytics engineers to transform data in their warehouses by writing select statements, and turns these select statements into tables and views. Dbt does the transformation (T) in extract, load, transform (ELT) processes – it does not extract or load data, but is designed to be performant at transforming data already inside of a ...
InterMine is an open source data warehouse system, licensed under the LGPL 2.1. InterMine is used to create databases of biological data accessed by sophisticated web query tools. InterMine can be used to create databases from a single data set or can integrate multiple sources of data.
Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.
DevLake: development data platform, providing the data infrastructure for developer teams to analyze and improve their engineering productivity; HugeGraph: a large-scale and easy-to-use graph database; KIE: community of solutions and supporting tooling for knowledge engineering and process automation, focusing on events, rules and workflows
Apache Iceberg is a high performance open-source format for large analytic tables.Iceberg enables the use of SQL tables for big data while making it possible for engines like Spark, Trino, Flink, Presto, Hive, Impala, StarRocks, Doris, and Pig to safely work with the same tables, at the same time. [1]
MonetDB is an open-source column-oriented relational database management system (RDBMS) originally developed at the Centrum Wiskunde & Informatica (CWI) in the Netherlands.It is designed to provide high performance on complex queries against large databases, such as combining tables with hundreds of columns and millions of rows.
The bus matrix purpose is one of high abstraction and visionary planning on the data warehouse architectural level. By dictating coherency in the development and implementation of an overall data warehouse the bus architecture approach enables an overall vision of the broader enterprise integration and consistency while at the same time dividing the problem into more manageable parts [2 ...
Most data integration tools skew towards ETL, while ELT is popular in database and data warehouse appliances. Similarly, it is possible to perform TEL (Transform, Extract, Load) where data is first transformed on a blockchain (as a way of recording changes to data, e.g., token burning) before extracting and loading into another data store. [14]