![]() It can easily perform queries in parallel, allowing users to get results within seconds. This interactive query tool is designed for fast performance with S3. Besides, there are no additional storage charges since the queries are performed directly in S3. So, users can significantly reduce their charges by partitioning, compressing, and converting their data into columnar formats. With Athena, users only have to pay for the queries they run and the amount of data scanned per each query. The interactive query service allows data analysts to tap into their data in Amazon S3 without creating processes to extract, transform, and load the data. Additionally, the customer doesn’t have to worry about failures, software updates, or scaling the servers or data warehouses as the datasets and number of users grow. ServerlessĪs mentioned above, Athena is serverless which means the user can quickly query data without having to configure or manage any infrastructure. This allows Athena to run quick ad-hoc analysis as well as more complex requests including nested queries, large joins, windows functions, and arrays. It also supports a wide range of data formats including Avro, Parquet, CSV, JSON, and ORC. ![]() Benefits of Amazon AthenaĪthena uses Presto, an SQL query engine that was designed to run interactive analytic queries against data sources of all sizes. To reduce the cost, Amazon advises users to use compressed data files, have data in columnar formats, and routinely delete old result sets. How much does Amazon Athena cost?Īmazon Athena pricing is $5 to scan Terabyte data from S3, surrounded by the closest megabyte having a minimum of 10 MB per query. You only need to point to your data in S3, configure the schema, and start the query. Thus, it simplifies the process – you run the query from an easy-to-use web console. ![]() Instead, with Athena, your query can run without using ETL. The difference here is that you’re now using cloud computing services instead of a search engine.Īmazon Athena does not require setup or configuration, which is typically the case with a local data store and involves an ETL (Extract, Transform, Load) preparing data in a database for a query by isolating the dataset. A query is similar to a Google search in that you can create the parameters for the SQL query that you need to perform. ![]() You might know the data is out there, but sometimes it’s hard to find the data sets that you actually need. One way to think about Athena? It’s somehow similar to a Google search. Athena uses a distributed SQL engine, Presto in order to run queries, Apache Hive to create and alter tables and partitions. How does Amazon Athena work?Īmazon Athena works directly with S3 data. Athena scales automatically running queries in parallel, therefore results are fast, even with large datasets or complex queries. Athena is serverless, so there is no infrastructure to set up or manage. ![]()
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