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Amazon Redshift
Amazon Redshift

623
310
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86
Apache Kudu
Apache Kudu

26
39
+ 1
3
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Amazon Redshift vs Kudu: What are the differences?

Amazon Redshift: Fast, fully managed, petabyte-scale data warehouse service. 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; Kudu: Fast Analytics on Fast Data. A columnar storage manager developed for the Hadoop platform. A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

Amazon Redshift belongs to "Big Data as a Service" category of the tech stack, while Kudu can be primarily classified under "Big Data Tools".

"Data Warehousing" is the top reason why over 27 developers like Amazon Redshift, while over 2 developers mention "Realtime Analytics" as the leading cause for choosing Kudu.

Kudu is an open source tool with 789 GitHub stars and 263 GitHub forks. Here's a link to Kudu's open source repository on GitHub.

- 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 Apache Kudu?

A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.
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    What are some alternatives to Amazon Redshift and Apache Kudu?
    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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    Decisions about Amazon Redshift and Apache Kudu
    Ankit Sobti
    Ankit Sobti
    CTO at Postman Inc · | 10 upvotes · 63K views
    atPostmanPostman
    dbt
    dbt
    Amazon Redshift
    Amazon Redshift
    Stitch
    Stitch
    Looker
    Looker

    Looker , Stitch , Amazon Redshift , dbt

    We recently moved our Data Analytics and Business Intelligence tooling to Looker . It's already helping us create a solid process for reusable SQL-based data modeling, with consistent definitions across the entire organizations. Looker allows us to collaboratively build these version-controlled models and push the limits of what we've traditionally been able to accomplish with analytics with a lean team.

    For Data Engineering, we're in the process of moving from maintaining our own ETL pipelines on AWS to a managed ELT system on Stitch. We're also evaluating the command line tool, dbt to manage data transformations. Our hope is that Stitch + dbt will streamline the ELT bit, allowing us to focus our energies on analyzing data, rather than managing it.

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    Reviews of Amazon Redshift and Apache Kudu
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    How developers use Amazon Redshift and Apache Kudu
    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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