The Amazon Athena Overview

Amazon Web Services ( AWS) released Amazon Athena (AWS Athena) in November 2016, a modern app that uses Facebook Presto, an ANSI-standard SQL to access the engine directly from Amazon Quick Storage Facility, or Amazon S3.

Amazon claims AWS Athena is flexible enough to help large-scale projects while at the same time remaining open to smaller businesses that only need to operate a few queries a month. The acceptance of Athena was quite high and the usage of cases was convincing. For eg, organizations are building serverless business intelligence stacks with Athena, Apache Parquet, and Tableau.

Amazon Athena:

Amazon defines AWS Athena as an open, serverless database application. What makes Athena so fascinating is that a serverless approach will change how other people think about their application workflows.

Because Athena accesses data directly from S3, users do not need to suggest setting up any servers, databases, clusters, or resources other than loading data to S3. There may be a cost reduction for usage in situations that do not need a conventional data center.

Here are a few main offers from AWS Athena:

  • An easy point-and-click framework for database and table formation is accessible without the requirement for specialized technological training typical of such programs.
  • Quickly test responses without needing to think about modifying queries or designing database frameworks.
  • As Amazon S3 stores data, corporations do not need to invest in physical IT infrastructure to access and store their records.
  • Amazon Athena billing is a pay-as-you-go operating model that ensures customers just need to compensate for the requests they currently perform. This prevents being tied into set prices with the quality of service that they do not really need.

All of these features make AWS Athena stand out and simple to use for large and small businesses, particularly if they are either using or preparing to use AWS S3.

Let's move to Amazon Athena:

To have started with AWS Athena, you will have to make sure that you have S3-based files. For your data in place, you would need to build a database and tables in a format that fits those found on S3.

Athena embraces formats such as CSV, ORC, XML, Apache Parquet, and more. If your data is not in one of the licensed formats on S3, you would need to convert it. Don’t be overwhelmed by the database and table development process. It’s a pretty easy method, and Amazon provides you with a step-by-step guide on how to build databases and tables and get started with queries.

You will save commonly used questions while you work with Athena. You may also access and archive the details of your Athena Catalog Manager application. Visit the AWS Documentation page for more detail about how Athena functions.

How to Query Athena

Amazon Athena provides companies a simple-to-use enterprise-level data analysis method. As businesses will not have to spend in network build-up and pay just for what they need, Athena is expected to become a strong and open part of the corporate data workflow.

The details of the queries will be sent back to S3. Managers and data scientists can always use an Amazon product named Amazon QuickSight to generate visualizations and reports. It is also practicable to use other business intelligence or BI resources, as well as programmatically via Python, Java, or similar, using a JDBC link (get a JDBC driver).

this is just basic information about AWS Athena, hope this blog will be helpful for you. keep reading!!!!!




We make your business smarter and broader through the power of the internet. Researcher | Web developer | Internet of things | AI |

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