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What is Amazon Athena?
Unlike conventional database queries, interactive queries enable data scientists to query large datasets efficiently and quickly. The interactive query services provided by leading cloud service providers help data scientists to query large datasets rapidly. The data scientists have the option to choose from a wide range of interactive query services according to the targeted cloud platform.
Amazon Athena was launched by Amazon Web Services (AWS) as an interactive query service. The businesses can use Amazon Athena as a sophisticated tool to query and analyze a large amount of data stored in Amazon Simple Storage Service (Amazon S3). They can further analyze the large datasets using a widely used database computing language – Structured Query Language.
Understanding Important Aspects of Amazon Athena
- Serverless Architecture: Like other new age cloud-based tools, Amazon Athena supports serverless architecture. The serverless architecture enables businesses to use the interactive query service efficiently without maintaining, scaling, and upgrading servers. The businesses can leverage serverless architecture to access and use Athena without building and maintaining onsite IT infrastructure.
- Standard SQL Support: Amazon Athena enables programmers to analyze large volumes of data stored in Amazon S3 by running SQL queries. At present, SQL is one of the standard languages for querying relational databases. SQL is used widely by software programmers to store, retrieve, and manipulate data stored in relational databases. Hence, any professional proficient in SQL can use Athena to analyze data stored in Amazon S3.
- Accelerates and Simplifies Large Dataset Analysis: Unlike other interactive query services, Athena does not require programmers to perform complex ETL jobs while preparing the large datasets for analysis. Any programmers with SQL skill can use the service to analyze large datasets quickly and efficiently. They can start interactive querying simply by pointing Athena to specific datasets in Amazon S3 and defining the schema. Athena further delivers results within a few seconds.
- Use Widely Used Big Data Tools: In addition to analyzing large data sets using SQL, the developers also have the option to work with a number of widely used big data solutions including Looker, AWS QuickSight, and Tableau Software. These big data tools help programmers to simplify data visualization, data analysis, and data reporting. Many developers these days form serverless analytics stack by combining Amazon Athena, AWS S3, and Tableau.
- Option to Integrate: The programmers even have the option to integrate Athena with AWS Glue Data Catalog. AWS Glue makes it easier for users to prepare and load data for analysis. The programmers can integrate Athena with AWS Glue Data Catalog to transform data and improve performance. The integration further helps users to discover schema by crawling varying data source, unify metadata repository across AWS services, and maintain multiple schema versions.
- Scalability: Amazon Athena is designed as a scalable and extensible interactive query service. It accelerates query execution by accessing compute resources across multiple facilities. It even has the capability to route the queries automatically and appropriately when a specific facility is unavailable. Athena further boosts query execution by using Amazon S3 as the underlying data store. The infrastructure provided by S3 focus on improving data storage and durability.
- Cost: The businesses can use Amazon Athena based on a price-per-query pricing model. Hence, they need to pay only for the TB of data scanned by the query. Athena requires users to pay for canceled queries based on the amount of data scanned. But the user can execute create a table, alter table, or drop table statements without incurring additional charges. The users must remember that Athena uses S3 as the underlying data store. They need to pay extra charges store, access, and transfer data stored in S3 while using Athena.
While working with AWS, the data scientists can leverage Amazon Athena as a robust interactive query service. The business can use Amazon Athena without creating and managing any infrastructure. They can further use the interactive query service based on a price-per-query pricing model. Hence, Amazon Athena enables businesses to simplify and accelerate analysis large volumes of data stored in Amazon S3 without increasing upfront and ongoing expenses.
