In this digital era, there are many cloud-based services that help us store and manage large volumes of data. Among such services, AWS has several storage and analytics services that are widely used by businesses. Among these services, one of the most popular is Amazon Athena.
What if you could analyze unstructured data (e.g., log files, documents, or text) in a scalable cloud environment? Sounds like something that you cannot wait to do? Well, there is good news for you! AWS Athena is an analytical database service that makes it simple to query data stored in Amazon S3 buckets and other accessible data sources.
In this blog post, we will cover everything you need to know about AWS Athena, including its features, pricing, pros and cons of using the service, and how to get started using it.
What is AWS Athena?
AWS Athena or Amazon Athena is a serverless query service. It allows users to query data stored in S3 buckets and other accessible data sources. The service was launched in late 2017, but it is still an evolving product that offers many features that are not yet available in all regions.
AWS Athena is a successor of AWS Glue, and it is designed to provide a scalable, cost-effective approach to data analysis. It is a query engine that processes data from S3, Amazon EMR, Amazon Redshift, Oracle, etc. It also supports a variety of formats, including CSV, JSON, and ORC.
In addition, it is a serverless product — which means that you don’t need to provision any hardware to run the service.
Why Use AWS Athena?
AWS Athena is a fully managed query service that allows you to quickly analyze data in S3 with standard SQL. It makes it simple to scale up your data analysis, without requiring you to provision any hardware or handle any of the logistics of running your own data processing cluster. It also offers built-in security features, like auditing and fine-grained access control.
With AWS Athena, you can query data stored in your Amazon S3 buckets. You can also use it to query data stored in Amazon Redshift, Amazon EMR, and Oracle databases. You can also use the service to query data that is stored on other data sources that are accessible through a JDBC connection.
Pricing of AWS Athena
Like all other Amazon Web Services products, is charged based on the amount of data that you process and the number of queries that you run.
You can get significant cost savings and performance gains by compressing, partitioning, or converting your data to a columnar format, because each of those operations reduces the amount of data that Athena needs to scan to execute a query.
Price per Query:
Example: For US North California Region:
- $6.75 per TB of data scanned
You are charged for the number of bytes scanned by Amazon Athena aggregated across all data sources, rounded up to the nearest megabyte, with a 10MB minimum per query.
The pricing is based on two factors – the amount of data that you want to analyze and the number of queries that you want to run.
You to choose between three pricing tiers.
- Tier 1 – For occasional analysis of small amounts of data
- Tier 2 – For frequent analysis of moderate amounts of data
- Tier 3 – For active analysis of large amounts of data
How to use Amazon Athena?
To use AWS Athena, you need to create an AWS Athena account. After creating the account, you need to create a data source and a notebook. Once you have created both of these, you can submit an SQL query to analyze your data.
To create a data source, navigate to the AWS Athena console and select “create data source” from the “operations” menu. In the dialog box that appears, select “S3” from the “data source type” drop-down menu and provide the name of your S3 bucket.
You can also select “Redshift” to connect to an Amazon Redshift cluster. To create a notebook, select New > Notebook from the AWS Athena console’s “operations” menu. In the dialog box that appears, select “Regular” from the “notebook type” drop-down menu.
Key Features of Amazon Athena
- Scalable Data Processing Using Lambda: Users can process unstructured data stored in S3 buckets and other data sources using the Lambda function of AWS Athena.
- End-to-End Encryption: It provides end-to-end encryption when accessing data stored in an S3 bucket.
- Auditing: It provides auditing capabilities that allow you to view various details about the activities performed using the service.
- Fine-grained Access Control: Users can use fine-grained access control to restrict data access.
- Open Source: AWS Athena is an open source product.
- Easy to use: It is easy to use, as it supports standard SQL.
- Pay per query: pay only for the data scanned by each query.
- Fast performance,: Automatically executes queries in parallel, to get query results in seconds, even on large datasets.
- Highly Durable: Athena uses Amazon S3 as its underlying data store, making your data highly available and durable.
Pros and Cons of Using AWS Athena
Pros:
- Quickly analyze data: You can quickly analyze data using AWS Athena. This is because it offers a scalable data processing service that does not require you to provision any hardware.
- Support for standard SQL: It supports standard SQL, which makes it easier to analyze data.
- Open source: It is an open source product, which means that you can view the source code of the product to understand how it works.
- Encryption: It provides end-to-end encryption when accessing data stored in an S3 bucket.
- Fine-grained access control: It allows you to use fine-grained access control to restrict data access.
- Auditing: Athena provides auditing capabilities that allow you to view the activities performed using the service.
- Easy to use: Athena is easy to use, as it supports standard SQL.
Cons:
- Requires an AWS account: You need an AWS account to use AWS Athena.
- Data in S3 buckets: The service works only with data stored in an S3 bucket.
- No support for structured data: does not support structured data, such as data in relational databases.
Conclusion
AWS Athena is an analytical database service that makes it simple to query data stored in Amazon S3 buckets and other accessible data sources. It allows users to quickly analyze data in S3 with standard SQL. It also offers built-in security features, like auditing and fine-grained access control. If you want to get started analyzing data in the cloud, you should definitely consider using AWS Athena. It is a great way to scale up your data analysis and eliminate the need to provision any hardware.
Related Posts:
- What is AWS Glue? A beginners to understanding Amazon’s New Data Processing Service in 2022
- What is AWS Systems Manager?
- What is a Cloud Architect? And How Do You Become One In 2022?
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