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Qubole VS Apache Spark for Azure HDInsight

Compare Qubole VS Apache Spark for Azure HDInsight and see what are their differences

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Qubole logo Qubole

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Apache Spark for Azure HDInsight logo Apache Spark for Azure HDInsight

This article provides an introduction to Spark in HDInsight and the different scenarios in which you can use Spark cluster in HDInsight.
  • Qubole Landing page
    Landing page //
    2023-06-22
  • Apache Spark for Azure HDInsight Landing page
    Landing page //
    2023-03-17

Qubole videos

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Fast and Cost Effective Machine Learning Deployment with S3, Qubole, and Spark

More videos:

  • Review - Migrating Big Data to the Cloud: WANdisco, GigaOM and Qubole
  • Review - Democratizing Data with Qubole

Apache Spark for Azure HDInsight videos

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Category Popularity

0-100% (relative to Qubole and Apache Spark for Azure HDInsight)

Qubole

Apache Spark for Azure HDInsight

Data Dashboard
78 78%
Data Dashboard
22% 22
Data Warehousing
71 71%
Data Warehousing
29% 29
Big Data
75 75%
Big Data
25% 25
Technical Computing
100 100%
Technical Computing
0% 0

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What are some alternatives?

When comparing Qubole and Apache Spark for Azure HDInsight, you can also consider the following products

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

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