Data analysis is challenging, and organizations continue to make attempts at making it easier.
The answers that businesses require from their data can be difficult to come by. Even though today’s world lives in an era where data is abundant, particularly with the shift to cloud storage, the tools for analyzing and processing that data are not always simple to use, accessible, or even effective. You must store data someplace, and most businesses must consider how they will do it.
Numerous analytics tools are available, including Amazon Athena (or AWS Athena).
This article will discuss the following:
What is Amazon Athena?
Amazon Athena is a web-based cloud storage tool that allows data analysts to run interactive searches in Amazon Simple Storage Service (S3). Large-scale data sets stored in Amazon S3 get used with Athena.
With use cases like data storage, archiving, website hosting, data backup and recovery, and application hosting for deployment, Amazon S3 was intended to make web-scale computing easier for developers. Amazon Athena allows customers to analyze data in Amazon S3 using standard SQL or Structured Query Language. The software is intended for ad hoc querying and complex analysis.
A data analyst can also use the AWS Management Console, an application programming interface, or a Java Database Connectivity driver to connect to Athena. The analyst can then design the schema and execute SQL queries on S3 data using the built-in query results editor.
The Advantages of the Amazon Athena Architecture
Here are some of the most prominent advantages of the Athena Database Software:
- The Serverless Architecture cuts IT Costs: Because Amazon Athena is serverless, users do not have to worry about managing or configuring infrastructure. It is as easy as running queries to use Athena, and you only pay for the Athena queries you run.
- Amazon Athena is SQL-based: There is no learning curve for users already proficient in SQL to use Athena to conduct SQL queries on the needed table. This table gets configured in the Glue Data Catalog, or data sources you may connect to using the Athena Query Federation SDK.
- AWS Athena packs good security capabilities: It is now feasible to create fine-grained access control in Amazon Athena, thanks to the launch of AWS Lake Formation. You can specify which users have access to which data and which operations.
What is an Amazon Athena Database?
The announcement of Athena, an ANSI-standard query tool or interactive query service that works with “big data” stored in Amazon S3, has sparked much interest from Amazon Web Services (AWS).
Because it is serverless, there is no infrastructure to worry about, and you can use S3’s scalable storage. This option also implies that you only pay for the queries you perform, which is advantageous for a data analyst who wants to keep Athena expenditures to a minimum.
Here are the things to know about the Amazon Athena Database:
Schema and Table Definitions
One of the primary benefits of an interactive query service is that your datasets get separated from the compute (query) infrastructure. Thus, you will need to create a database and tables with S3 data.
Data Formats
The query service supports various formats, including ORC, JSON, CSV, and Parquet. Amazon recommends using Apache Parquet to transform data to columnar storage formats.
Ensure your team is aware of this improvement, as separating compute and storage is a key component of an interactive query service. Using a compressed and columnar format can help you save money on queries and storage while boosting performance.
Speed and Performance
AWS makes it simple to conduct Athena queries on S3 data without the need to set up servers, create clusters, or perform any other housekeeping that other query systems necessitate.
Supported Functions
As previously stated, Athena’s SQL query engine is PrestoDB, open-source software. Users can use this tool to interact directly with Amazon S3 data using ANSI-standard SQL. This feature contains relational operators like JOIN and ordinary SQL functions like SELECT.
Limitations
There are certain drawbacks. The following, for example, are not supported:
- Stored procedures and user-defined functions
- Transactions via Hive or Presto
Although support for LZO has gotten added, Amazon has implemented several query restrictions. For example, you can only allow users to submit one query per account while performing five concurrent inquiries.
But, is Athena a Database?
Depending on the business and technological situation, you can use Athena instead of traditional databases. However, it is essential to consider the distinctions between the two and why you might prefer one over the other.
Athena is a query engine rather than a database. That is to say:
- Separate Compute and Storage: Databases keep data in a state of rest and provide the resources needed to perform queries and calculations. On the other hand, Athena does not retain data; instead, all storage gets controlled by Amazon S3.
- There is no DML interface: There is no need to model the data using Athena. I/O is a bottleneck in almost every database, but this is not an issue with Athena, so you can devote all of your compute resources to query processing. If your requirements are to change data, you should be looking elsewhere.
- Speed: Athena is not suitable for most transactional uses as it is not as fast as such.
Creating an Athena Database
In Athena, a database is a logical grouping of tables you construct. It is simple to create a database in the Athena console query editor.
To use the Athena query editor to construct a database, follow these steps:
- Go to https://console.aws.amazon.com/athena/ to access the Athena console.
- Enter the Hive Data Definition Language (DDL) command CREATE DATABASE myDatabase on the Editor tab. Replace myDatabase with the name of the database that you would like to utilize.
- Press Ctrl+ENTER or choose Run.
- Select your database from the Database menu on the left of the query editor to make it the current database.
Summary
Data has become a company’s most valuable asset, acquiring insights and extracting more value from it than ever. Amazon Athena is a great tool for querying structured & semi-structured data as part of your data lake, but for transactional purposes you should look elsewhere.
Athena Security With Satori
Satori enables you to enforce security policies such as dynamic data masking and row-level security on your Athena data access. In addition, Satori continuously discovers and classifies sensitive data, enables self-service data access to datasets on Athena and other data platforms, and keeps an enriched audit log on all data accessed through Athena.
