Amazon Athena vs Google BigQuery

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Amazon Athena
Amazon Athena

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Google BigQuery
Google BigQuery

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Amazon Athena vs Google BigQuery: What are the differences?

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; Google BigQuery: Analyze terabytes of data in seconds. 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 belongs to "Big Data Tools" category of the tech stack, while Google BigQuery can be primarily classified 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 "High Performance" was stated as the key factor in picking Google BigQuery.

According to the StackShare community, Google BigQuery has a broader approval, being mentioned in 156 company stacks & 39 developers stacks; compared to Amazon Athena, which is listed in 47 company stacks and 17 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 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.
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    What are some alternatives to Amazon Athena and Google BigQuery?
    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.
    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.
    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.
    See all alternatives
    Decisions about Amazon Athena and Google BigQuery
    Snowflake
    Snowflake
    Google BigQuery
    Google BigQuery

    I use Google BigQuery because it makes is super easy to query and store data for analytics workloads. If you're using GCP, you're likely using BigQuery. However, running data viz tools directly connected to BigQuery will run pretty slow. They recently announced BI Engine which will hopefully compete well against big players like Snowflake when it comes to concurrency.

    What's nice too is that it has SQL-based ML tools, and it has great GIS support!

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    Google BigQuery
    Google BigQuery
    Amazon Athena
    Amazon Athena

    I use Amazon Athena because similar to Google BigQuery , you can store and query data easily. Especially since you can define data schema in the Glue data catalog, there's a central way to define data models.

    However, I would not recommend for batch jobs. I typically use this to check intermediary datasets in data engineering workloads. It's good for getting a look and feel of the data along its ETL journey.

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    Interest over time
    Reviews of Amazon Athena and Google BigQuery
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    How developers use Amazon Athena and Google BigQuery
    Avatar of ShareThis
    ShareThis uses Google BigQueryGoogle BigQuery

    BigQuery allows our team to pull reports quickly using a SQL-like queries against our large store of data about social sharing. We use the information throughout the company, to do everything from making internal product decisions based on usage patterns to sharing certain kinds of custom reports with our publishers.

    Avatar of Lyndon Wong
    Lyndon Wong uses Google BigQueryGoogle BigQuery

    Aggregation of user events and traits across a marketing website, SaaS web application, user account provisioning backend and Salesforce CRM. Enables full-funnel analysis of campaign ROI, customer acquisition, engagement and retention at both the user and target account level.

    Avatar of Blue Shell Games
    Blue Shell Games uses Google BigQueryGoogle BigQuery

    Google's insanely fast, feature-rich, zero-maintenance column store. Used for real-time customer data queries.

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    How much does Google BigQuery cost?
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