Amazon EMR vs Qubole

Amazon EMR
Amazon EMR

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Qubole
Qubole

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Amazon EMR vs Qubole: What are the differences?

What is Amazon EMR? Distribute your data and processing across a Amazon EC2 instances using Hadoop. Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year.

What is Qubole? Prepare, integrate and explore Big Data in the cloud (Hive, MapReduce, Pig, Presto, Spark and Sqoop). Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon EMR and Qubole belong to "Big Data as a Service" category of the tech stack.

Some of the features offered by Amazon EMR are:

  • Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster
  • Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.
  • Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.

On the other hand, Qubole provides the following key features:

  • Intuitive GUI
  • Optimized Hive
  • Improved S3 Performance

"On demand processing power" is the top reason why over 13 developers like Amazon EMR, while over 9 developers mention "Simple UI and autoscaling clusters" as the leading cause for choosing Qubole.

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What is Amazon EMR?

Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year.

What is Qubole?

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Want advice about which of these to choose?Ask the StackShare community!

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      Amazon EC2
      Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.
      Amazon DynamoDB
      All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
      Hadoop
      The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
      Amazon Redshift
      Redshift makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
      Google BigQuery
      Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
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        Pinterest uses QuboleQubole

        We ultimately migrated our Hadoop jobs to Qubole, a rising player in the Hadoop as a Service space. Given that EMR had become unstable at our scale, we had to quickly move to a provider that played well with AWS (specifically, spot instances) and S3. Qubole supported AWS/S3 and was relatively easy to get started on. After vetting Qubole and comparing its performance against alternatives (including managed clusters), we decided to go with Qubole

        Avatar of Andrew La Grange
        Andrew La Grange uses Amazon EMRAmazon EMR

        We use Amazon EMR for all our Hadoop workloads.

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