Amazon Redshift vs Google BigQuery vs Qubole

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Amazon Redshift

1.3K
1.1K
+ 1
103
Google BigQuery

1.2K
1K
+ 1
146
Qubole

33
97
+ 1
67
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Pros of Amazon Redshift
Pros of Google BigQuery
Pros of Qubole
  • 37
    Data Warehousing
  • 27
    Scalable
  • 16
    SQL
  • 14
    Backed by Amazon
  • 5
    Encryption
  • 1
    Cheap and reliable
  • 1
    Isolation
  • 1
    Best Cloud DW Performance
  • 1
    Fast columnar storage
  • 27
    High Performance
  • 24
    Easy to use
  • 21
    Fully managed service
  • 19
    Cheap Pricing
  • 16
    Process hundreds of GB in seconds
  • 11
    Full table scans in seconds, no indexes needed
  • 11
    Big Data
  • 8
    Always on, no per-hour costs
  • 5
    Good combination with fluentd
  • 4
    Machine learning
  • 13
    Simple UI and autoscaling clusters
  • 10
    Feature to use AWS Spot pricing
  • 7
    Optimized Spark, Hive, Presto, Hadoop 2, HBase clusters
  • 7
    Real-time data insights through Spark Notebook
  • 6
    Hyper elastic and scalable
  • 6
    Easy to manage costs
  • 6
    Easy to configure, deploy, and run Hadoop clusters
  • 4
    Backed by Amazon
  • 4
    Gracefully Scale up & down with zero human intervention
  • 2
    All-in-one platform
  • 2
    Backed by Azure

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Cons of Amazon Redshift
Cons of Google BigQuery
Cons of Qubole
    Be the first to leave a con
    • 1
      You can't unit test changes in BQ data
      Be the first to leave a con

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      What is 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.

      What is 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.

      What is Qubole?

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

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      Jobs that mention Amazon Redshift, Google BigQuery, and Qubole as a desired skillset
      What companies use Amazon Redshift?
      What companies use Google BigQuery?
      What companies use Qubole?

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      What tools integrate with Amazon Redshift?
      What tools integrate with Google BigQuery?
      What tools integrate with Qubole?

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      Aug 28 2019 at 3:10AM

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      What are some alternatives to Amazon Redshift, Google BigQuery, and Qubole?
      Amazon Athena
      Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
      Amazon DynamoDB
      With it , 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.
      Amazon Redshift Spectrum
      With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data.
      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.
      Microsoft Azure
      Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacenters. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment.
      See all alternatives