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Qubole

Prepare, integrate and explore Big Data in the cloud (Hive, MapReduce, Pig, Presto, Spark and Sqoop)
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What is Qubole?

Qubole is a cloud based service that makes big data easy for analysts and data engineers.
Qubole is a tool in the Big Data as a Service category of a tech stack.

Who uses Qubole?

Companies
5 companies reportedly use Qubole in their tech stacks, including Pinterest, KeepTruckin, and SaleCycle.

Developers
30 developers on StackShare have stated that they use Qubole.
Pros of Qubole
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Simple UI and autoscaling clusters
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Feature to use AWS Spot pricing
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Optimized Spark, Hive, Presto, Hadoop 2, HBase clusters
7
Real-time data insights through Spark Notebook
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Hyper elastic and scalable
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Easy to manage costs
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Easy to configure, deploy, and run Hadoop clusters
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Backed by Amazon
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Gracefully Scale up & down with zero human intervention
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All-in-one platform
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Backed by Azure

Qubole's Features

  • Intuitive GUI
  • Optimized Hive
  • Improved S3 Performance
  • Auto Scaling
  • Spot Instance Pricing
  • Managed Clusters
  • Cloud Integration
  • Cluster Lifecycle Management

Qubole Alternatives & Comparisons

What are some alternatives to Qubole?
Databricks
Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.
Snowflake
Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
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.
Amazon Redshift
It is optimized for data sets 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.
Amazon EMR
It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
See all alternatives

Qubole's Followers
104 developers follow Qubole to keep up with related blogs and decisions.