Amazon Redshift vs Qubole vs Treasure Data

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Amazon Redshift
Amazon Redshift

747
447
+ 1
86
Qubole
Qubole

20
30
+ 1
51
Treasure Data
Treasure Data

16
22
+ 1
5
- No public GitHub repository available -
- No public GitHub repository available -
- No public GitHub repository available -

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 Treasure Data?

Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market.
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        What are some alternatives to Amazon Redshift, Qubole, and Treasure Data?
        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.
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        How developers use Amazon Redshift, Qubole, and Treasure Data
        Avatar of Pinterest
        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 Olo
        Olo uses Amazon RedshiftAmazon Redshift

        Aggressive archiving of historical data to keep the production database as small as possible. Using our in-house soon-to-be-open-sourced ETL library, SharpShifter.

        Avatar of Christian Moeller
        Christian Moeller uses Amazon RedshiftAmazon Redshift

        Connected to BI (Pentaho)

        Avatar of Kovid Rathee
        Kovid Rathee uses Amazon RedshiftAmazon Redshift

        OLAP and BI

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