Introduction to Amazon Athena Service

Amazon Athena is a quick, interactive query service that allows you to analyze data using standard SQL quickly. Athena is an interactive data analysis tool that uses interactive data analysis to handle complex queries in a few minutes. It is a serverless system. As a result, there is no hassle in getting started, and no infrastructure management is needed. 

Amazon Athena does not provide a database service. As a result, you must pay for the queries you run. Simply point your data in S3, define the schema required, and you’re ready to go with standard SQL.

Table of Content

• What was the need for Athena?
• Features of Athena
• Benefits of Athena
• Limitations of Athena
• Pricing of Athena
• Working of Athena
• Use Cases for Athena
• Difference between Athena and Microsoft SQL Server
• Difference between Athena and Redshift

What was the need for Amazon Athena?

Earlier, when Amazon did not launch Athena, data analysts or developers didn’t have any tools for data analytics.They have to work manually or use other means to analyze the data stored on S3. This was becoming a significant problem.

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On November 20, 2016, Amazon launched Athena. Now, data analysts have a tool to play with their data. Athena helps them analyze unstructured, semi-structured, and structured data stored on S3. Using Athena, they can also create dynamic queries for your dataset.

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Features of Athena

There are various features of Athena. But let’s discuss some of those features here:

1. Athena is simple to implement because it does not need installation.
2. Because it is serverless, the end-user does not have to worry about infrastructure, configuration, scaling, or failure.
3. Athena only charges you for the query you run, not for the amount of data managed per query.
4. Athena is a lightning-fast analytics tool. It can run complex queries in less time.
5. Athena gives you great control of the data set.
6. Athena is highly available, and users can run queries around the clock.
7. The best feature of Athena is its ability to integrate with AWS Glue. AWS Glue will assist the user in creating a more unified data archive. 
8. Athena uses Presto, an open-source, distributed SQL query engine optimized for low latency.

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Benefits of Athena

There are many benefits of Athena. Let’s go through some of those benefits:

1. Utilizing Athena does not require users to monitor or manually provision resources.
2. Integration with other AWS services (support 24 hours a day, seven days a week).
3. Athena supports open-source formats like JSON, CSV, and Apache.
4. Role-based access control is integrated across all AWS services.
5. API audit logging and security that is comprehensive and cross-service.
6. Data is stored in Amazon S3 by Athena. Hence the costs are massively lower than storing the same amount of data in a coupled database. 
7. Architectural patterns/guidance and training (well-architected).

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Limitations of Athena

As every coin has two sides, there are also some limitations of Amazon Athena. Some of those limitations are:

1. Queries are the only ones that can be optimized.
2. Without indexing options, Athena’s operation load increases, affecting performance.
3. Data must first be partitioned in order for efficient queries to be possible.
4. Presto federated connectors, stored procedures, and parameter-based queries are not supported.
5. Athena may time out when querying a table with thousands of partitions.
6. Source files that begin with an underscore or a dot are considered hidden.
7. The maximum row and column size are 32 megabytes.

Pricing of Amazon Athena

You have to pay for the queries which you run with Amazon Athena. You are billed depending on the amount of data that each query scans. Compressing or transforming your data to a columnar format can significantly cost savings and performance gains.

These processes minimize the amount of data Athena must scan to execute a query. You will be charged $5.00 per TB of data reviewed/scanned in the Asia Pacific region (Mumbai).

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Working of Amazon Athena

Amazon Athena functions with S3 data directly. Athena employs Presto’s distributed SQL engine to execute queries and Apache Hive to create and modify tables and partitions.

It is similar to a Google search in specific ways. You may be aware that the data exists, but it can be challenging to locate your required data. A query is comparable to a Google search.

You can specify the parameters for the SQL query you want to run. The distinction here is that you utilize cloud computing services rather than a search engine.

Amazon Athena does not require any installation or configuration. As a result, it simplifies the process because the query is run from a user-friendly web console. You have to point to your data in S3, customize the schema, and run the query.

Let’s go over the prerequisites for working with Athena:

1. AWS account is a must.
2. Allow your account to export cost and usage data to an S3 bucket.
3. Prepare buckets for Athena to connect. Every time AWS writes to a bucket, it generates a manifest file based on the metadata.
4. Create an Athena folder within the bucket that contains only the data.
5. We can use a single region to simplify the setup.
6. The final step is to download the new IAM user’s credentials.

Use Cases for Amazon Athena

Some of the everyday use cases of Athena are:

• Redshift cost reduction:

While Redshift provides quite high performance, it is a coupled database. This database could become complex and expensive to operate at larger scales. In these cases, Athena and S3 storage can minimize some Redshift expenses.

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• Streaming analytics:

Querying and visualizing real-time or near-real-time streaming sources such as web click-streams.

• Ad-hoc analytics on big data:

Rapidly answering a particular query that usually requires scanning terabytes of data.

Difference between Amazon Athena and Microsoft SQL Server

There are many differences between Athena and Microsoft SQL Server. But, for better clarity, let’s go through the differences in a tabular format.

Difference between Athena and Redshift

There are many differences between Athena and Redshift. But, for better clarity, let’s go through the differences in a tabular format.

Conclusion

Athena is serverless, which means it can be easily scaled based on system load. It employs the open-source Presto, a distributed SQL engine for querying and analyzing large amounts of data as a backend. If you want to learn more about AWS services or tools, you can refer to the following articles:

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