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Databricks, Inc. is a global data, analytics, and artificial intelligence (AI) company, founded in 2013 by the original creators of Apache Spark. [ 1 ] [ 4 ] The company provides a cloud-based platform to help enterprises build, scale, and govern data and AI, including generative AI and other machine learning models.
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...
SQL script, CSV, TSV or the above in zip (as a plugin); imports of server-site file in SQL or SQL in zip, gzip or bzip2: SQL script, CSV, TSV or the above in zip, gzip, bzip2; XML (as a plugin) No Git: Altova DatabaseSpy: No No Yes CSV, XML XML, XML Structure, CSV, HTML, MS Excel No ? Database Workbench: Yes No Yes Yes Yes Yes Yes [15] DataGrip ...
Spark: Databricks: Data analytics framework 2.4.3 Apache Spark: 2014 Spring Framework: SpringSource: Software development framework 5.1.9 Spring 2002 Squiz Squiz.net Enterprise content management system v4.8.2 (PHP5) Squiz Matrix 1998 StarOffice: Oracle Corporation: Office productivity suite 8.0 OpenOffice.org 2000 Sun Studio: Oracle Corporation
Tool Supported data models (conceptual, logical, physical) Supported notations Forward engineering Reverse engineering Model/database comparison and synchronization
The GQL project is led by Stefan Plantikow (who was the first lead engineer of Neo4j's Cypher for Apache Spark project) and Stephen Cannan (Technical Corrigenda editor of SQL). They are also the editors of the initial early working drafts of the GQL specification. [6]
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.
Scala runs on the Java platform (Java virtual machine) and is compatible with existing Java programs. [15] As Android applications are typically written in Java and translated from Java bytecode into Dalvik bytecode (which may be further translated to native machine code during installation) when packaged, Scala's Java compatibility makes it well-suited to Android development, the more so when ...