Amazon Athena seems to be saving the day in many businesses nowadays.
Data solutions can be difficult to find for businesses. Data is definitely abundant, especially through the mainstream implementation of cloud storage technology, but finding the right solutions for analyzing and processing data can be tough.
Some solutions are hard to use, while others simply aren’t very efficient. Data needs to be stored and managed, so only the best tools will do for today’s scaling business.
This is where Amazon Athena comes in. This query service makes it possible for businesses to run their own SQL queries as if they have their own local data centers. This serverless technology could be highly beneficial to organizations that don’t want to deal with infrastructure management and need something fast and user-friendly.
In this guide, we’ll break down the basics of Amazon Athena and its use cases for your own organization.
It is not as complex as it may seem. In fact, this service can be implemented in a majority of organizations for a variety of use cases.
What is Amazon Athena?
Amazon Athena is an interactive query service from Amazon. It’s based on Apache Presto, an open-source distributed SQL query engine. This service makes it possible to analyze data directly stored within Amazon S3 through the use of ANSI SQL.
It is also serverless, meaning that it lacks an infrastructure that requires ongoing maintenance and management. As a result, users only need to pay for the queries they run.
Use Cases of Amazon Athena
There are many use cases for Amazon Athena. To start, this platform is excellent for companies that need to analyze data stored in Amazon S3. If you have unstructured or structured data, such as CSV, JSON, etc., this service can be quite helpful. You can easily use Athena to run your own ad-hoc queries via ANSI SQL without having to aggregate or load your data into the Athena platform.
Just as well, Athena makes data visualization a breeze. Most businesses and organizations need data visualization for a wide range of use cases, from sales trends to marketing success measurements. Athena can easily generate reports and explore your data with intuitive BI tools and SQL clients that are connected to a JDBC and/or ODBC driver.
Athena can also integrate with the AWS Glue Data Catalog from the Amazon Web Services. This provides consistent metadata storage for data inside of Amazon S3. As a result, you can make tables and generate query data based on your metadata stored in your Amazon Web Services account.
Pros and Cons of Amazon Athena
As with any new technology, Amazon Athena has its pros and its cons.
Pros
There are so many benefits in using Athena, which include:
- Only costs $5 per TB of data scanned per query.
- No setup fee is required.
- Installation and implementation are intuitive and easy.
- Can query with a browser-based system.
- Highly compatible with other software, which is a huge business intelligence benefit for established businesses.
- Dashboards are easy to read and visual.
- All data can be kept in native formats.
- Reports are extremely easy to generate in real-time.
- Makes it possible to work with basically any data source in a wide range of formats.
- Can easily analyze CSV files for reporting.
- All data can be queries without the need to run servers.
- Ideal for small businesses and startups with little in the way of development resources.
- It’s very scalable.
- Can query and analyze a wide variety of files in SQL, including JSON.
- Perfect for users who optimize their data compression and utilize column stores.
- Management and maintenance are kept at a minimum on the user side.
- Ad hoc checks are a breeze compared to other similar services.
- Glue crawlers can provide a simplified data catalog.
- No configuration is required.
Cons
Athena, while excellent, isn’t perfect. A few downsides include:
- Doesn’t offer a free trial or freemium version to try ahead of time.
- Doesn’t offer premium integration services.
- Not as complex as other similar services, which might be problematic for organizations that need additional features.
- Small-scale data sets work well, but organizations may struggle with large data sets.
- While Amazon Athena is scalable, there are some limitations that make scaling less than seamless.
Amazon Athena - Final Thoughts
In the end, Amazon Athena is a great database querying solution for a majority of organizations. If infrastructure management isn’t possible, especially for small businesses and startups, this solution is worth looking into.
How Can Yurbi Help?
Amazon Athena offers an ODBC connector that can be used to connect and visualize your data in other business intelligence tools, such as Yurbi.
Why would you do that? Yurbi offers a few great use cases when combined with Amazon Athena.
Self-Service BI - allows internal and external (i.e.) customers the ability to create their own reports and visualizations without needing to write or know ANSI SQL query writing.
Security - apply dynamic data-level security, so users are able to view and build new reports, but only in the context of a data constraint such as a tenant, customer, department, location, region, or other parameter.
Multi-data source - combine data stored in Amazon Athena with other internal (or external) databases and API endpoints. Yurbi can pull data from multiple sources, combine that in memory, and then allow you to create reports from the joined source.
White-Label Embedding - use Yurbi as your embedded analytics presentation layer to accelerate providing advanced reports and dashboard within your own SaaS App.
Price - compared to other similar BI tools such as Power BI, Tableau, and Domo, Yurbi is a fraction of the price.
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What do you think about Amazon Athena and its use cases? Tell us what you think about this platform in the comments section below!