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2. Databricks - Wikipedia

   en.wikipedia.org/wiki/Databricks

   Databricks develops and sells a cloud data platform using the marketing term "lakehouse", a portmanteau of "data warehouse" and "data lake". [40] Databricks' Lakehouse is based on the open-source Apache Spark framework that allows analytical queries against semi-structured data without a traditional database schema. [41]

3. Data lake - Wikipedia

   en.wikipedia.org/wiki/Data_lake

   Data lakehouses are a hybrid approach that can ingest a variety of raw data formats like a data lake, yet provide ACID transactions and enforce data quality like a data warehouse. [ 14 ] [ 15 ] A data lakehouse architecture attempts to address several criticisms of data lakes by adding data warehouse capabilities such as transaction support ...

4. DBRX - Wikipedia

   en.wikipedia.org/wiki/DBRX

   DBRX is an open-sourced large language model (LLM) developed by Mosaic ML team at Databricks, released on March 27, 2024. [1] [2] [3] It is a mixture-of-experts transformer model, with 132 billion parameters in total. 36 billion parameters (4 out of 16 experts) are active for each token. [4]

5. Exclusive: Databricks is expanding the scope of its AI ... - AOL

   www.aol.com/finance/exclusive-databricks...

   Databricks’ new venture capital fund, which officially launches today, will focus on a broader subset of companies that are sitting on top or working along with the Databricks Data Intelligence ...

6. Streaming data - Wikipedia

   en.wikipedia.org/wiki/Streaming_data

   A data lake refers to the storage of a large amount of unstructured and semi data, and is useful due to the increase of big data as it can be stored in such a way that firms can dive into the data lake and pull out what they need at the moment they need it, [3] whereas a data stream can perform real-time analysis on streaming data, and it ...

7. 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 ...