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  2. Databricks - Wikipedia

    en.wikipedia.org/wiki/Databricks

    Databricks grew out of the AMPLab project at University of California, Berkeley that was involved in making Apache Spark, an open-source distributed computing framework built atop Scala. The company was founded by Ali Ghodsi , Andy Konwinski, Arsalan Tavakoli-Shiraji, Ion Stoica , Matei Zaharia , [ 8 ] Patrick Wendell, and Reynold Xin .

  3. Apache Spark - Wikipedia

    en.wikipedia.org/wiki/Apache_Spark

    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 ...

  4. Plotly - Wikipedia

    en.wikipedia.org/wiki/Plotly

    Dash Enterprise connects to major big data backends, including Salesforce, PostgreSQL, Databricks via PySpark, Snowflake, Dask, Datashader, and Vaex. [39] In 2020, Plotly partnered with NVIDIA to integrate Dash with RAPIDS, [ 40 ] and NVIDIA participated in Plotly’s Series C funding round.

  5. Lazy evaluation - Wikipedia

    en.wikipedia.org/wiki/Lazy_evaluation

    In programming language theory, lazy evaluation, or call-by-need, [1] is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which avoids repeated evaluations (by the use of sharing).

  6. Jaro–Winkler distance - Wikipedia

    en.wikipedia.org/wiki/Jaro–Winkler_distance

    In computer science and statistics, the Jaro–Winkler similarity is a string metric measuring an edit distance between two sequences. It is a variant of the Jaro distance metric [1] (1989, Matthew A. Jaro) proposed in 1990 by William E. Winkler.

  7. Amazon DocumentDB - Wikipedia

    en.wikipedia.org/wiki/Amazon_DocumentDB

    Amazon DocumentDB is a managed proprietary NoSQL database service that supports document data structures, with some compatibility with MongoDB version 3.6 (released by MongoDB in 2017) and version 4.0 (released by MongoDB in 2018). As a document database, Amazon DocumentDB can store, query, and index JSON data. It is available on Amazon Web ...