Amazon Redshift vs Qubole vs Snowflake

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Amazon Redshift

1.5K
1.4K
+ 1
108
Qubole

35
104
+ 1
67
Snowflake

1.1K
1.2K
+ 1
27
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Pros of Amazon Redshift
Pros of Qubole
Pros of Snowflake
  • 41
    Data Warehousing
  • 27
    Scalable
  • 17
    SQL
  • 14
    Backed by Amazon
  • 5
    Encryption
  • 1
    Cheap and reliable
  • 1
    Isolation
  • 1
    Best Cloud DW Performance
  • 1
    Fast columnar storage
  • 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
  • 7
    Public and Private Data Sharing
  • 4
    Multicloud
  • 4
    Good Performance
  • 4
    User Friendly
  • 3
    Great Documentation
  • 2
    Serverless
  • 1
    Economical
  • 1
    Usage based billing
  • 1
    Innovative

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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 Qubole?

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

What is 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.

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

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What tools integrate with Amazon Redshift?
What tools integrate with Qubole?
What tools integrate with Snowflake?

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What are some alternatives to Amazon Redshift, Qubole, and Snowflake?
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 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.
See all alternatives