Amazon Athena vs SingleStore

by Gralio Feb 20, 2025

Both platforms offer powerful data analysis, but cater to different needs. Athena suits occasional analysis of S3-stored data, while SingleStore targets real-time, high-performance applications needing diverse data handling and hybrid workloads.

At Gralio.ai we help to simplify your decision-making process by offering detailed, side-by-side software comparisons like this one, to help you confidently choose the tool that aligns with your business goals.

This comparison was created by analysing 355 reviews and 60 websites, saving 2 hours, 28 minutes of reading.

Amazon Athena

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SingleStore

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About

Amazon Athena is a service that lets you analyze large datasets stored in Amazon S3 using standard SQL queries. It's serverless, so there's no infrastructure to manage, and you pay only for the queries you run. This makes it a cost-effective way to get insights from your data without the complexity of traditional data warehousing.

SingleStore is a database platform designed for speed and handling large amounts of data, making it suitable for applications requiring real-time analytics. It allows businesses to manage various data formats in one place, simplifying data infrastructure. SingleStore is used by companies of all sizes across various industries, notably in finance and technology.

Summary

Main difference

Amazon Athena excels in serverless, pay-per-query data analysis within the AWS ecosystem, directly querying data stored in S3. SingleStore prioritizes real-time analytics and hybrid transactional/analytical processing, supporting diverse data formats and workloads.

Relative strengths of Amazon Athena (compared to SingleStore)

Cost-effective, pay-per-query pricing, ideal for ad-hoc analysis.
Directly queries S3 data, simplifying data access and eliminating ETL.
Serverless architecture; no infrastructure management needed.

Relative weaknesses of Amazon Athena (compared to SingleStore)

Performance can lag for complex queries on very large datasets.
Limited SQL syntax compared to full-featured databases.
Primarily focused on S3; integrating other data sources can be challenging.

What companies are using Amazon Athena and SingleStore?

No data

Who should use Amazon Athena VS. SingleStore

Amazon Athena is a serverless query service ideal for analyzing large datasets in Amazon S3 using standard SQL. Users praise its ease of use and cost-effectiveness, especially for those familiar with SQL. However, some have noted occasional performance issues with very large datasets and limitations in SQL syntax support. It's a good fit for anyone needing a quick and easy way to analyze data in S3 without managing infrastructure.

SingleStore is a powerful real-time database platform ideal for businesses needing fast analytics on large datasets. Its speed and scalability make it a good choice for companies of all sizes, from startups to large enterprises, particularly in finance and technology. Key features include cloud database services, hybrid search, and SQL support.

Best for small to enterprise-level companies seeking efficient data analysis.
Suitable for various data-heavy industries needing scalable and cost-effective analytics.

Ideal for small to enterprise-level businesses, especially those with 100-1000+ employees.
A strong fit for Finance, Banking, Insurance, and Software/IT companies.

Amazon Athena and SingleStore features

Supported

Partially supported

Not supported

Type in the name of the feature or in your own words tell us what you need

Hybrid vector and full-text search

Partially supported

Athena supports hybrid search indirectly via integration with OpenSearch Service.

Supported

SingleStore supports hybrid vector and full-text search using SQL.
Cloud database service for real-time workloads

Not supported

Athena is not designed for real-time transactional workloads or combining transactional and analytical processing.

Supported

SingleStoreDB is a cloud database service designed for real-time workloads, combining transactions and analytics.
Faster JSON analytics

Partially supported

Athena supports JSON analytics but doesn't explicitly claim faster performance compared to traditional methods.

Supported

SingleStoreDB supports faster JSON analytics for real-time insights.
SQL support

Supported

Athena supports standard SQL queries, including complex analyses like large joins and window functions.

Supported

SingleStore supports SQL for querying data, including ANSI SQL.
NoSQL support

Partially supported

Athena supports querying NoSQL databases like MongoDB via DocumentDB.

Partially supported

SingleStore can query data ingested from NoSQL databases like MongoDB, but not query them directly.
Cloud-based deployment

Supported

Athena is deployed and managed within the AWS cloud environment.

Supported

SingleStore supports cloud deployments, including a managed service called SingleStore Helios.

Qualities

Value and Pricing Transparency

+1

Strongly positive sentiment

No data
Customer Service

+0.33

Rather positive sentiment

+0.5

Rather positive sentiment
Ease of Use

+0.64

Rather positive sentiment

+0.43

Rather positive sentiment
Reliability and Performance

+0.67

Rather positive sentiment

+0.71

Strongly positive sentiment
Ease of Implementation

+0.6

Rather positive sentiment

+0

Neutral sentiment
Scalability

+1

Strongly positive sentiment

+1

Strongly positive sentiment

Amazon Athena and SingleStore Pricing

No data

User sentiment

Strongly positive

See full Pricing page

No data

See full Pricing page

Amazon Athena and SingleStore review insights

355 reviews analysed from and

Users love

Serverless architecture; no infrastructure management needed.
Cost-effective, pay-per-query pricing model.
Easy to use for users familiar with SQL.
Fast query execution for smaller datasets.
Directly queries data in S3 without requiring ETL.

Excellent scalability and versatility for multi-model architectures.
Comprehensive and responsive customer support.
Combines row and column store benefits effectively.
Fast data processing and tooling.
High throughput for real-time aggregates and individual row retrieval.

Users dislike

Occasional performance lags, especially with large datasets.
Limited SQL syntax support; some standard features are missing.
Error messages could be more informative and precise.
UI/UX could be improved, particularly for query history and navigation.
Limited integration with other data sources besides S3.

Difficult to debug issues and requires extensive back-and-forth with support.
Tedious tasks like updating enum columns.
Slow pipelines with limited logging.
Replication at the table level is lacking.
Lack of a reject file for pipeline loading errors.

Amazon Athena and SingleStore Ratings

Glassdoor

3.7/5

(206324)

Glassdoor

4.0/5

(379)

Company health

Employee growth

11% increase in the last year

10% increase in the last year

Web traffic

10% increase in the last quarter

9% decrease in the last quarter

Financing

No data

June 2022 - $464M

How do Athena's and SingleStore's SQL dialects differ for complex queries?

Athena uses ANSI SQL, supporting common SQL features but with some limitations, especially regarding less common functions and syntax. SingleStore also uses SQL (including ANSI SQL) but extends it with proprietary functions and features optimized for real-time analytics and specific data types like JSON and geospatial data. Therefore, complex queries in SingleStore might utilize these extensions for performance or functionality not available in Athena's stricter SQL dialect. Porting complex queries between the two may require modifications.

Which product better supports real-time analytics on S3-stored data?

While both products offer analytical capabilities, SingleStore is better suited for real-time analytics on S3-stored data. Although Athena allows querying data directly in S3, it's optimized for ad-hoc querying and not specifically designed for real-time analysis. SingleStore, with its focus on speed and handling large datasets for real-time workloads, provides a more suitable platform for this purpose. It should be noted that integrating SingleStore with S3 might require additional ETL processes, unlike Athena's native integration.

What are the advantages of Amazon Athena?

Amazon Athena offers several advantages. Its serverless architecture eliminates infrastructure management and reduces costs with its pay-per-query pricing model. It's easy to use for those familiar with SQL and offers fast query execution, especially for smaller datasets, directly querying data in S3 without needing ETL. This makes it highly accessible and cost-effective for ad-hoc data analysis.

What are the disadvantages of Amazon Athena?

Amazon Athena's disadvantages include occasional performance lags with large datasets, limited SQL syntax support compared to traditional databases, and less informative error messages. The user interface/user experience could be improved, especially for query history and navigation. Finally, it has limited integration with data sources other than Amazon S3.

Alternatives to Amazon Athena and SingleStore

Microsoft SQL Server

Microsoft SQL Server is a database management system for businesses of all sizes. It helps you analyze various types of data and can be used in multiple environments, including on your servers and in the cloud. SQL Server offers high performance and strong security features. It allows developers to build applications using different programming languages and provides mobile business intelligence tools.

MongoDB Atlas

MongoDB Atlas is a cloud-based database service that's easy for developers to use. It allows you to store information in flexible formats that are like digital filing cabinets. It's designed for businesses of all sizes and can handle various data needs. MongoDB Atlas is reliable, adapts to changes easily, and can grow with your company's needs by spreading information across multiple servers.

BoilingData

BoilingData is a cloud-based analytics tool that lets you analyze large datasets stored in Amazon S3 without moving or pre-processing them. It's designed for companies struggling with slow and expensive analytics from large datasets. BoilingData speeds up analysis by only loading the necessary data when needed, allowing for interactive exploration of your data. It's cost-effective because you only pay for the time your queries are running. BoilingData also offers data sharing features with secure access control for collaboration.

LeanXcale

LeanXcale is a database solution designed for speed and scalability. It handles both massive data sets and real-time information, making it suitable for various uses like operational reporting, analysis, and machine learning. LeanXcale aims to process transactions quickly and efficiently, particularly for financial services, through its unique technology. While supporting standard data management features, LeanXcale emphasizes its ability to handle large volumes of information quickly and efficiently.

QuestDB

QuestDB is an open-source database designed specifically for handling large volumes of time-stamped data, like financial records or sensor readings. It boasts very fast performance, even with massive datasets, making it suitable for applications requiring real-time analysis. QuestDB supports standard SQL queries and integrates with popular data visualization tools for easy analysis. It’s built to be cost-effective, performing well on both modest and powerful hardware.

Snowflake

Snowflake is a cloud-based data platform designed for businesses to store, manage, and analyze large amounts of data. It works like a giant, virtual warehouse for all your data, accessible from anywhere. Snowflake adapts to your needs, scaling its power and cost up or down on demand. This makes it suitable for tasks like analyzing customer trends, building data-driven applications, or sharing data securely with partners. Its strength lies in handling massive datasets with high speed and efficiency.

Page co-authored by

Michal Kaczor

CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

Tymon Terlikiewicz

CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.

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