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Amazon Redshift
Amazon Redshift

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Druid
Druid

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Amazon Redshift vs Druid: What are the differences?

Developers describe Amazon Redshift as "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. On the other hand, Druid is detailed as "Fast column-oriented distributed data store". Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Amazon Redshift can be classified as a tool in the "Big Data as a Service" category, while Druid is grouped under "Big Data Tools".

"Data Warehousing" is the primary reason why developers consider Amazon Redshift over the competitors, whereas "Real Time Aggregations" was stated as the key factor in picking Druid.

Druid is an open source tool with 8.32K GitHub stars and 2.08K GitHub forks. Here's a link to Druid's open source repository on GitHub.

According to the StackShare community, Amazon Redshift has a broader approval, being mentioned in 270 company stacks & 68 developers stacks; compared to Druid, which is listed in 24 company stacks and 12 developer stacks.

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What is Amazon Redshift?

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.

What is Druid?

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
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Why do developers choose Amazon Redshift?
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      What are some alternatives to Amazon Redshift and Druid?
      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 Druid
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      How developers use Amazon Redshift and Druid
      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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