Amazon Athena vs Amazon Redshift

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Amazon Athena vs Amazon Redshift: What are the differences?

What is Amazon Athena? Query S3 Using SQL. 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.

What is 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.

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

"Use SQL to analyze CSV files" is the primary reason why developers consider Amazon Athena over the competitors, whereas "Data Warehousing" was stated as the key factor in picking Amazon Redshift.

Lyft, Coursera, and 9GAG are some of the popular companies that use Amazon Redshift, whereas Amazon Athena is used by Auto Trader, Zola, and Twilio SendGrid. Amazon Redshift has a broader approval, being mentioned in 269 company stacks & 67 developers stacks; compared to Amazon Athena, which is listed in 50 company stacks and 18 developer stacks.

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What is 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.

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.
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      What are some alternatives to Amazon Athena and Amazon Redshift?
      Presto
      Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
      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.
      Cassandra
      Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
      Spectrum
      The community platform for the future.
      Amazon Quicksight
      Amazon QuickSight is a fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data.
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      Decisions about Amazon Athena and Amazon Redshift
      Ankit Sobti
      Ankit Sobti
      CTO at Postman Inc · | 10 upvotes · 74.1K 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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      How developers use Amazon Athena and Amazon Redshift
      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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