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A Comparative Analysis of Amazon Athena and Azure Synapse Analytics


In the fast-paced world of cloud-based data analytics, organizations constantly seek effective and scalable solutions to gain insights from their data. The two main products in this space are Amazon Athena and Azure Synapse Analytics, which Amazon Web Services and Microsoft Azure provide. In this blog, we will compare these platforms and examine their features, capabilities, and suitability for different uses.

Amazon Athena

Amazon Athena is a serverless interactive query service that allows users to analyze data stored in Amazon S3 using standard SQL queries. There is no development or management at Amazon Athena. You point Amazon Athena to your Amazon S3 bucket, define your idea, and start querying your products. This serverless architecture offers unmatched flexibility and capacity, allowing users to focus on making sense of their data without worrying about infrastructure management.

One of Amazon Athena’s best features is its pay-per-query model; This means you only pay for the queries you run. This affordable price makes Athena an attractive choice for organizations with different project requirements or looking to improve cost performance. Additionally, Amazon Athena integrates with other AWS services, such as AWS Glue for data cataloging and AWS Lake Formation for data lake management.

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Azure Synapse Analytics

Azure Synapse Analytics is a powerful service that combines big data and data storage into a single platform. Azure Synapse Analytics allows customers to ingest, organize, manage, and present data for their immediate BI and automation needs. Azure Synapse Analytics supports serverless and hosted services with its integrated analytics platform, allowing organizations to measure compute and storage as needed independently.

One of the main features of Azure Synapse Analytics is integration with Azure Data Lake Storage Gen2, which provides a unified database for storing structured, semi-structured, and unstructured data. Additionally, Azure Synapse Analytics can create data visualizations through Power BI integration, allowing users to gain insight from their information by creating interactive dashboards and reports.

Scenarios where Amazon Athena can be used

  • Organizations can use Azure Athena to analyze large amounts of log data generated by multiple sources, including web servers and firewalls. By querying data stored in Amazon S3, security analysts can identify potential security vulnerabilities, detect vulnerabilities, and investigate.
  • Companies that maintain data repositories in Amazon S3 can use Amazon Athena to perform queries and analysis across different data types. For example, retailers can analyze customer history, web traffic data, and data stored in Amazon S3 to gain customer insights, develop business strategies, and forecast demand.
  • Organizations with low or unknown workloads can benefit from Amazon Athena’s cost-per-query model. They can use Amazon Athena to execute on-demand SQL queries against data in Amazon S3 without having to set up and manage infrastructure and pay only for the queries they execute.

Scenarios where Azure Synapse Analytics can be used

  • Azure Synapse Analytics is ideal for organizations needing dynamic and flexible data storage to collect and analyze big, semi-structured data. For example, telecommunications companies can use Azure Synapse Analytics to create a central data warehouse to store and analyze customer data, calls, and performance metrics.
  • In healthcare and life sciences industries, Azure Synapse Analytics can analyze large amounts of data generated by clinical trials and data from a patient’s letter. Data scientists and researchers can use Azure Synapse Analytics to perform complex research tasks, derive insights, and accelerate clinical research and drug discovery processes.
  • Organizations in retail, e-commerce, and online gaming industries can benefit from the instant measurement capabilities of Azure Synapse Analytics. By capturing and processing data from sources such as IoT devices, social media platforms, and online marketing, companies can quickly gain insight into consumer behavior, analyze situations, and make decisions from the data.


Amazon Athena and Azure Synapse Analytics are two platforms that work on cloud data analytics, each offering unique features and capabilities to meet the different needs of the organization. Amazon Athena is known for its serverless architecture, pay-as-you-go pricing, and seamless integration in the AWS ecosystem.

At the same time, Azure Synapse Analytics provides an integrated analytics platform that includes big data and data storage capabilities in the Azure ecosystem. By carefully analyzing their needs and considering the advantages of each platform, organizations can choose the solution that best suits their needs in terms of data analysis and business goals.

Drop a query if you have any questions regarding Amazon Athena or Azure Synapse Analytics and we will get back to you quickly.

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1. Can I use Amazon Athena with data stored in Azure Blob Storage?

ANS: – Yes, Amazon Athena supports external tables, allowing users to query data stored in Azure Blob Storage using Athena’s SQL interface. This enables cross-cloud data analytics scenarios and facilitates seamless data integration between AWS and Azure environments.

2. Does Azure Synapse Analytics support serverless querying like Amazon Athena?

ANS: – Yes, Azure Synapse Analytics offers serverless querying capabilities through its serverless SQL pool, allowing users to analyze data on-demand without needing provisioned resources.

3. Can I visualize data directly from Amazon Athena or Azure Synapse Analytics?

ANS: – Yes, both Amazon Athena and Azure Synapse Analytics offer integration with data visualization tools such as Power BI, Tableau, and Looker. Users can create interactive dashboards and reports to visualize insights from their data, facilitating data-driven decision-making across the organization.

WRITTEN BY Lakshmi P Vardhini



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