I have used both across a few different use cases and conclude:
Advantages of Redshift Spectrum:
- Allows creation of Redshift tables
- Able to join Redshift tables with Redshift spectrum tables efficiently
If you do not need those things then you should consider Athena as well
Athena differences from Redshift spectrum:
- Billing. This is the major difference and depending on your use case you may find one much cheaper than the other
- Performance. I found Athena slightly faster.
- SQL syntax and features. Athena is derived from presto and is a bit different to Redshift which has its roots in postgres.
- Connectivity. Its easy enough to connect to Athena using API,JDBC or ODBC but many more products offer "standard out of the box" connection to Redshift
Also, for either solution, make sure you use the AWS Glue metadata, rather than Athena as there are fewer limitations.
Answer from Jon Scott on Stack OverflowChaosSearch
chaossearch.io › blog › when-to-deploy-aws-redshift-or-athena-use-cases
AWS Redshift vs AWS Athena: Best Use Cases for Each
April 29, 2024 - Another way to think about the differences between Redshift and Athena is to focus on the varying use cases that each service lends itself to. Examples of use cases that are a good fit for Redshift include: Event log analytics: Cloud application and event logs are an example of structured, consistent data that is easy to analyze within Redshift clusters. Real-time analytics: AWS Redshift can be integrated with data stream processing services like Amazon Kinesis to enable near real-time analysis of large-scale data streams.
Reddit
reddit.com › r/aws › redshift vs athena
r/aws on Reddit: Redshift vs Athena
May 11, 2022 -
I'm building a web service via API Gateway that would allow users to run queries on a DB. The data is in S3 and I thought of using Athena and have Lambda run queries against it. Thing is, I see a lot of similar designs but with Redshift instead of Athena. One of our Principal Engineers said Redshift fits better for a web service compared to Athena (but I didn't ask why). Any idea why it's the case?
EDIT: for context the data in S3 is parquet and it is partitioned. I'm expecting a moderate number of users using the API.
Top answer 1 of 5
35
Athena queries are asynchronous. Your API call starts the query and returns that it's been successfully requested. In order to get the data, you need to poll the query status and then read the results from S3. Athena's latency is also comparable high, since it loads your data from S3 into a temporary environment for every query. Between those two, Athena doesn't tend to be a good fit for a REST API.
2 of 5
9
Redshift isnt serverless, so you'll have to have it running 730 hours a month to ensure round-the-clock service.
What is the difference between Athena and Redshift?
Athena is a serverless query service that allows you to analyze data directly from S3 using SQL, whereas Redshift is a fully managed cloud data warehouse optimized for large-scale complex queries and analytics.
hevodata.com
hevodata.com › home › blog › data warehousing
Amazon Redshift Vs Athena: Compare On 7 Key Factors
Why Redshift is better?
Redshift is better for structured, long-term analytics workloads, offering faster performance, scalability, and integration for advanced use cases like machine learning.
hevodata.com
hevodata.com › home › blog › data warehousing
Amazon Redshift Vs Athena: Compare On 7 Key Factors
Is Athena a data warehouse?
No, Athena is not a data warehouse; it is a query engine. It doesn’t store data but queries data stored in S3 or external sources.
hevodata.com
hevodata.com › home › blog › data warehousing
Amazon Redshift Vs Athena: Compare On 7 Key Factors
Videos
01:00
Redshift vs Athena: Which AWS Tool Fits Your Data Strategy? | #AWS ...
02:02
Athena Vs Redshift - a detailed comparison ⚖️ - YouTube
21:45
Difference between Athena and Redshift Spectrum - YouTube
07:58
Interactive and Federated Querying using Amazon Athena and Redshift ...
02:36
Amazon Athena vs Redshift - YouTube
06:08
Redshift Spectrum vs Amazon Athena #aws #awstutorial #cloud - YouTube
RisingWave
risingwave.com › blog › aws-athena-vs-redshift-which-is-more-cost-effective
AWS Athena vs Redshift: Which is More Cost-Effective? - RisingWave: Real-Time Event Streaming Platform
AWS Athena and Amazon Redshift stand out as two powerful data services in the cloud analytics landscape. AWS Athena Pricing offers a serverless, pay-per-query model, making it highly cost-effective for ad-hoc queries and exploratory analysis.
Edge Delta
edgedelta.com › company › knowledge-center › athena-vs-redshift
Athena vs Redshift: Choosing the Right AWS Analytics Tool
May 6, 2025 - ... When it comes to data analytics ... very different purposes. Athena is a fully serverless query engine that lets you analyze data directly from Amazon S3 with no need to manage infrastructure....
Chartio
chartio.com › resources › tutorials › redshift-vs-athena
Redshift vs Athena | Tutorial by Chartio
June 6, 2016 - Redshift is best used for large and structured datasets. Athena is an interactive query service that allows you to conveniently analyze data stored in Amazon Simple Storage Service (S3) by using basic SQL.
Firebolt
firebolt.io › comparison › athena-vs-redshift
Athena vs Redshift | Performance & Pricing: Comparison Guide
Thus, 8 RPU is equivalent to 16 vCPU / 128GB RAM. The minimum RPU is 8. Athena is a shared multi-tenant resource, with no guarantees on the amount or availability of the resources allocated for your queries.
Top answer 1 of 5
31
I have used both across a few different use cases and conclude:
Advantages of Redshift Spectrum:
- Allows creation of Redshift tables
- Able to join Redshift tables with Redshift spectrum tables efficiently
If you do not need those things then you should consider Athena as well
Athena differences from Redshift spectrum:
- Billing. This is the major difference and depending on your use case you may find one much cheaper than the other
- Performance. I found Athena slightly faster.
- SQL syntax and features. Athena is derived from presto and is a bit different to Redshift which has its roots in postgres.
- Connectivity. Its easy enough to connect to Athena using API,JDBC or ODBC but many more products offer "standard out of the box" connection to Redshift
Also, for either solution, make sure you use the AWS Glue metadata, rather than Athena as there are fewer limitations.
2 of 5
16
This question has been up for quite a time, but still, I think I can contribute something to the discussion.
What is Athena?
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. (From the Doc)
Pretty straight forward, right?
Then comes the question of what is Redshift Spectrum and why Amazon folks made it when Athena was pretty much a solution for external table queries?
So, AWS folks wanted to create an extension to Redshift (which is pretty popular as a managed columnar datastore at this time) and give it the capability to talk to external tables(typically S3). But they wanted to make life easier for Redshift users, mostly analytics people. Many analytics tools don't support Athena but support Redshift at this time. But creating your Reshift cluster and storing data was a bottleneck. Again Redshift isn't that horizontally scalable and it takes some downtime in case of adding new machines. If you are a Redshift user, making your storage cheaper makes your life so much easier basically.
I suggest you use Redshift spectrum in the following cases:
You are an existing Redshift user and you want to store more data in Redshift.
You want to move colder data to an external table but still, want to join with Redshift tables in some cases.
- Spark unloading of your data and if you just want to import data to Pandas or any other tools for analyzing.
And Athena can be useful when:
- You are a new user and don't have Redshift cluster. Access to Spectrum requires an active, running Redshift instance. So Redshift Spectrum is not an option without Redshift.
- As Spectrum is still a developing tool and they are kind of adding some features like transactions to make it more efficient.
- BTW Athena comes with a nice REST API , so go for it you want that.
All to say Redshift + Redshift Spectrum is indeed powerful with lots of promises. But it has still a long way to go to be mature.
Hevo Data
hevodata.com › home › blog › data warehousing
Amazon Redshift Vs Athena: Compare On 7 Key Factors
December 30, 2024 - In Redshift, both compute and storage layers are coupled, however in Redshift Spectrum, compute and storage layers are decoupled. Athena is a serverless analytics service where an Analyst can directly perform the query execution over AWS S3.
Upsolver
upsolver.com › home › blog › athena or redshift? 4 questions to decide
Athena or Redshift? 4 Questions to Decide | Upsolver
May 28, 2024 - Redshift is the more natural choice for data warehouse reporting, Athena for ad-hoc queries against S3 storage. Redshift would be the better choice if you have data coming in from diverse sources and you would like to transform that data, enforce ...
AWS
docs.aws.amazon.com › amazon athena › user guide › what is amazon athena? › when should i use athena?
When should I use Athena? - Amazon Athena
The query engine in Amazon Redshift has been optimized to perform especially well on running complex queries that join large numbers of very large database tables. When you need to run queries against highly structured data with lots of joins across lots of very large tables, choose Amazon Redshift...
Swiftorial
swiftorial.com › matchups › aws › athena-vs-redshift
Matchups: Athena vs Redshift | Aws Comparison
August 22, 2025 - Athena offers serverless SQL queries on S3 data with Presto—example: query 1TB of logs in minutes. Redshift provides columnar storage, materialized views, and Spectrum—example: analyze 10TB of sales data.
Skeddly
blog.skeddly.com › 2018 › 01 › amazon-athena-vs-amazon-redshift.html
Amazon Athena vs. Redshift | Skeddly
If you want to quickly run queries at a low cost any time without needing to set up a complex infrastructure, opt for Amazon Athena. If you want to run high-performance complex queries using a scalable data warehouse for high-level reporting and business intelligence, choose Redshift.
TechTarget
techtarget.com › searchcloudcomputing › answer › Compare-EMR-Redshift-and-Athena-for-data-analysis-on-AWS
Compare Amazon Redshift, Athena and EMR for data analysis | TechTarget
Compare relevant aspects of Redshift, Athena and EMR. Amazon Athena, which is built on open source Trino, Presto and Spark engines, is a serverless service for data analysis on AWS.
Chariot Solutions
chariotsolutions.com › home › performance comparison: athena versus redshift
Performance Comparison: Athena versus Redshift — Chariot Solutions
November 21, 2023 - There are a couple of possible reasons; one is general query overhead as Redshift parses the query and develops the execution job. A more likely cause is the aggregation step, which happens on the (single-threaded) leader node. I’ll dig into this a little more in a future post. What’s more striking to me is the difference between Athena and Redshift Spectrum.
Integrate.io
integrate.io › blog › amazon-redshift-spectrum-vs-athena
Amazon Redshift Spectrum vs. Athena: A Detailed Comparison | Integrate.io
July 21, 2025 - In the case of Athena, the Amazon Cloud automatically allocates resources for your query. You do not have control over resource provisioning. Thus, performance can be slow during peak hours.
Upsolver
upsolver.com › home › blog › aws athena pricing vs. aws redshift pricing comparison
AWS Athena Pricing vs. AWS Redshift Pricing Comparison | Upsolver
May 28, 2024 - For ongoing high-volume queries that require consistent compute workloads, Redshift turns out to be a more reasonable choice. Athena charges are calculated based on the volume of data scanned during query execution.
Sprinkle Data
sprinkledata.com › blogs › athena-vs-redshift-unraveling-the-battle-of-cloud-data-warehouses
Amazon Athena vs. Amazon Redshift: Choosing the Right Data Warehousing Solution
March 15, 2024 - They can be effortlessly integrated with AWS Glue for ETL processing, AWS Lambda for serverless data transformations, and Amazon QuickSight for data visualization and business intelligence. Redshift's MPP architecture and compatibility with various BI tools make it a powerful choice for enterprises looking to build sophisticated data analytics pipelines and derive actionable insights. On the other hand, Athena's simplicity and compatibility with standard SQL enable users to interact with the data in S3 directly, eliminating the need for complex data transformations and enhancing the data exploration process
Xomnia
xomnia.com › home › athena vs redshift: why should you consider athena for your next aws data platform?
Athena vs Redshift: Why should you consider Athena for your next AWS data platform? - Xomnia
June 25, 2025 - Redshift has been a staple of AWS data platforms since its release, to the point where alternatives aren’t even considered by many teams. Redshift is a good choice for users who need to store and query large amounts of data, and who need a high-performance data warehouse solution. When the workloads join many tables together, the “data warehouse service” power will show itself against the columnar storage method of Athena.
Medium
blog.openbridge.com › how-is-aws-redshift-spectrum-different-than-aws-athena-9baa2566034b
How is AWS Redshift Spectrum different than AWS Athena? | Openbridge
April 8, 2021 - Why pay to store that data in Redshift, adjusting cluster size to hold more data when moving it to external tables on AWS S3 and query data with Spectrum is an option? This approach can minimize the need to scale Redshift requires a new node for improving consistent performance for both a simple or complex query, which can be expensive! Note: You are still paying “per query” for the amount of data scanned via Spectrum the same as Athena.