Hue vs Apache Spark: What are the differences?
Hue: An open source SQL Workbench for Data Warehouses. It is open source and lets regular users import their big data, query it, search it, visualize it and build dashboards on top of it, all from their browser; Apache Spark: Fast and general engine for large-scale data processing. Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Hue and Apache Spark can be primarily classified as "Big Data" tools.
Apache Spark is an open source tool with 22.9K GitHub stars and 19.7K GitHub forks. Here's a link to Apache Spark's open source repository on GitHub.
According to the StackShare community, Apache Spark has a broader approval, being mentioned in 356 company stacks & 564 developers stacks; compared to Hue, which is listed in 7 company stacks and 8 developer stacks.
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