AWS Lake Formation vs Snowflake Analytics comparison

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Amazon Web Services (AWS) and Snowflake Computing are both solutions in the Cloud Data Warehouse category. Amazon Web Services (AWS) is ranked #4 with an average rating of 8.1, while Snowflake Computing is ranked #11 with an average rating of 8.4. Amazon Web Services (AWS) holds a 3.3% mindshare in CDW, compared to Snowflake Computing’s 3.6% mindshare. Additionally, 85% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Snowflake Computing users who would recommend it.

AWS Lake Formation

Read 21 AWS Lake Formation reviews

2,858 Views
2,201 Comparison Views

85% willing to recommend

Snowflake Analytics

Read 44 Snowflake Analytics reviews

4,190 Views
1,718 Comparison Views

100% willing to recommend

AWS Lake Formation

Snowflake Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on Nov 8, 2026

AWS Lake Formation and Snowflake Analytics are leading solutions in the data management arena. AWS Lake Formation holds the advantage for cost-conscious businesses due to its lower initial setup costs and tight AWS ecosystem integration. Snowflake Analytics stands out for its advanced features and scalability, which justify its higher cost for businesses needing robust performance.

Features: AWS Lake Formation facilitates data lake simplification and security through automation, seamless AWS service integration, and fine-grained access control. It supports ETL processes and data cataloging with Glue Workflows and Blueprints without exposing sensitive data. Snowflake Analytics offers cloud-based scalability and flexible, decoupled storage and computation. It excels in data warehousing capabilities, providing advanced analytics features, easy multi-cloud deployment, and fast query performance.

Room for Improvement: AWS Lake Formation could enhance non-AWS user accessibility and streamline the process for initially unfamiliar users. User documentation and support beyond AWS native services can also be expanded. The complexity of setting permissions for newcomers might need simplification. Snowflake Analytics may improve its cost efficiency further for smaller-scale users. Addressing initial setup complexity and enhancing support for real-time analytics could broaden its appeal. Improving data governance features and reducing complexity in managing multiple cloud environments can enhance its functionality.

Ease of Deployment and Customer Service: Snowflake Analytics, with its cloud-native design, allows for straightforward deployment across AWS, Azure, and Google Cloud, further supported by excellent service and support. AWS Lake Formation is integrated within the AWS ecosystem, facilitating a convenient setup for AWS users, although it might present challenges for those less familiar with AWS frameworks.

Pricing and ROI: AWS Lake Formation offers lower initial setup costs, appealing to organizations focused on cost efficiency. It provides an effective solution for companies utilizing AWS without additional infrastructure costs. Snowflake Analytics involves higher upfront costs but provides long-term ROI with its advanced features, rapid scalability, and performance capabilities, making it an attractive choice for organizations seeking robust analytics power.

To learn more, read our detailed AWS Lake Formation vs. Snowflake Analytics Report (Updated: November 2026).

Buyer's Guide

AWS Lake Formation vs. Snowflake Analytics

November 2026

Download the complete report

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

AWS Lake Formation

Ranking in Cloud Data Warehouse

4th

Average Rating

8.0

Reviews Sentiment

5.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Snowflake Analytics

Ranking in Cloud Data Warehouse

11th

Average Rating

8.4

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Web Analytics (6th)

Mindshare comparison

As of November 2026, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 3.3%, down from 5.2% compared to the previous year. The mindshare of Snowflake Analytics is 3.6%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
AWS Lake Formation	3.3%
Snowflake Analytics	3.6%
Other	93.1%

Cloud Data Warehouse

Featured Reviews

Ciro Baldim Guerra

Sr Analytics Engineer at Itau Unibanco S.A.

Has improved data governance by enabling clear ownership and structured access across teams

In my company, Itaú, we don't utilize all AWS offerings due to rigorous security measures. We operate approximately six to eight months behind other available services. I'm uncertain if gaps exist because of this limitation, though the system functions effectively for us. AWS Lake Formation offers column-level access control for databases, but we haven't implemented this feature either because it hasn't been approved by our compliance, governance, or security areas. In our current setup, everyone from my business unit uses the same consumer account. When access is requested for a table, everyone using that business unit account receives access. This could present a security concern, though it benefits new team members who automatically receive all necessary access permissions. However, I struggle to identify specific improvements needed in AWS Lake Formation.

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Hemanthreddy Vakiti

Data Engineer at a tech vendor with 10,001+ employees

Daily restaurant dashboards have become faster and now support simultaneous team analytics

Some of the best features of Snowflake Analytics is how it is separated for compute and storage, which allows multiple teams to run queries without performance impact. Our project has more than nine or ten teams, so if a team is working on a particular dashboard and another team wants to work on Snowflake Analytics, they can easily work on it without disturbing the work of one team, ensuring that the work can be consistent and multiple users can use the tool simultaneously. This is one of the main features I appreciate about Snowflake Analytics.The other aspect is how the query performance is high due to its columnar storage and also automatic optimization, allowing for scaling down during weekdays when there is less data and scaling up during weekends or festivals when the data can be huge. Because of this automatic scaling, if there is less data, we are using only 5 GB instead of 10 GB, which reduces the storage level, and consequently, the cost can be reduced. This automatic scaling and optimization saves us a huge amount of money for our project. Snowflake Analytics has impacted our organization positively by providing faster query performance and better scalability. Previously, we faced issues with slow queries due to traditional systems, but within Snowflake, we can assign separate virtual warehouses for reporting as well as data processing, ensuring that it does not impact tool performance and does not delay reporting to business users. Analysts can run complex queries without affecting ETL workloads due to this separation, which has improved our speed of reporting, and our business users have expressed happiness due to how fast we are generating reports during peak hours.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The main benefits that I have seen from using AWS Lake Formation are related to FinOps because you have control of your data and can track your costs since AWS Lake Formation is integrated into a unique platform, which is AWS Cloud Service."

"The most valuable features of AWS Lake Formation were the access model itself, as it allows implementation of filters, Blueprints, and row-level and column-level security to mask data that shouldn't be accessed by certain entities, enabling granular control without exposing PII data."

"We have observed measurable benefits in terms of cost savings, time savings, resource savings, and efficiency improvements in our workflows."

"Every solution has its pros and cons, however, for our purposes, this solution works quite well for us."

"We use this to reduce latency from minutes to seconds, as we aim for real-time visibility into patient healthcare monitoring."

"AWS Lake Formation significantly improves the structure of the data mesh, making it superior to previous structures we used."

"A favorite feature of AWS Lake Formation is that it provides us with visibility into who has access to a particular table or database in Glue."

"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."

More AWS Lake Formation pros

"Snowflake Analytics is flexible in nature, allowing for the addition of more data tables without affecting the main structure."

"Snowflake Analytics has positively impacted our organization by saving about eight to ten hours per week, which we can use for advanced analytics and automation tasks."

"Very good flexibility and it offers computation completely decoupled from the storage."

"Snowflake Analytics is pretty easy to use with the connectors for integration with the tools and systems in my company."

"It is an all-in-one platform that provides the capabilities needed for various analytics tasks, including data warehousing for machine learning."

"It is quite a convenient tool."

"The computational power of Snowflake is very good."

"The most important feature is the warehouse functionality."

More Snowflake Analytics pros

Cons

"AWS Lake Formation's pricing could be cheaper."

"The initial onboarding process is challenging because creating a plan takes a month to a month and a half to build out."

"For the end-users, it's not as user-friendly as it could be."

"I think AWS Lake Formation could improve by enforcing the least privilege by design, moving from ad hoc grants to role-based access controls."

"I would appreciate online support, which I don't have access to in my corporation at the bank, so that is important."

"Athena can be a bit clunky when writing queries, indicating a potential enhancement point for easier user interaction with query tools such as DataGrip using provided driver JARs."

"In our experience what could be improved are not the support, performance or monitoring, but at a managerial level, the very expensive professional services of AWS. This could be an area of improvement for them. It's too expensive to acquire their support."

"You need to have data experience to use the product."

More AWS Lake Formation cons

"I cannot comment on the product's stability because we are still struggling with its performance."

"The platform's data governance space needs more capability."

"A room for improvement in Snowflake Analytics is Spark, particularly its connector for Spark. An additional feature I'd like to see in the next release of the solution is built-in analytics."

"Moving data from legacy systems to Snowflake is not that easy. There are some cases where processors are not actually compatible with Snowflake."

"As of now, I have not seen ROI from Snowflake Analytics."

"The product's cost is an area of concern where improvements are required."

"The pricing visibility is complex. If you understand pricing, you can estimate costs, but if not, it can be challenging."

"Integration into different Python and Jupyter notebooks needs to be improved."

More Snowflake Analytics cons

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."

"The pricing is on the higher side."

"Snowflake Analytics is not an expensive solution, and its pricing is average."

"The cost of Snowflake Analytics is low, any small organization can use it."

"The product's pricing is subjective."

"I have been using free trial version."

"The solution's price is high and I would rate it an eight out of ten."

"I rate the product price a seven on a scale of one to ten, where one is low price, and ten is high price."

"On a scale of one to ten, where one is a low price, and ten is a high price, I rate the pricing a seven. The solution's pricing is high."

More Snowflake Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Outsourcing Company

13%

Manufacturing Company

Construction Company

16%

Outsourcing Company

14%

Financial Services Firm

11%

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	2
Large Enterprise	15

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	13
Large Enterprise	23

Questions from the Community

What is your experience regarding pricing and costs for AWS Lake Formation?

I don't understand much about the pricing of AWS Lake Formation, but I know how to search for the cost of Glue jobs, and I use the calculator in Amazon. I use a tool to preview the cost based on th...

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What needs improvement with AWS Lake Formation?

Regarding areas of AWS Lake Formation that could be improved or enhanced, I prefer not to answer, mainly because I do not believe that I would be the most valuable person to ask, as I have not used...

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What is your primary use case for AWS Lake Formation?

My usual use cases for AWS Lake Formation involved securing and governing the data resources that we configured in AWS, but we did not use the analytics or machine learning capabilities specificall...

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What is your experience regarding pricing and costs for Snowflake Analytics?

The pricing for Snowflake Analytics is reasonable, but as I am not part of the management team, I am not certain about our organization's exact costs. Overall, the return on investment for this too...

See all answers

What needs improvement with Snowflake Analytics?

One improvement Snowflake Analytics could benefit from is in cost, particularly during peak hours. Sometimes, due to its automatic scalability, we think it has scaled up, but it does not always hap...

See all answers

What is your primary use case for Snowflake Analytics?

I am using Snowflake Analytics because we are already using Snowflake for data engineering and data warehousing tasks, and we are using it for analytics as well as business intelligence reporting. ...

See all answers

Comparisons

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Compared 12% of the time

Snowflake vs AWS Lake Formation

Compared 11% of the time

Azure Data Factory vs AWS Lake Formation

Compared 8% of the time

Databricks vs AWS Lake Formation

Compared 8% of the time

Teradata vs AWS Lake Formation

Compared 4% of the time

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Amplitude vs Snowflake Analytics

Compared 14% of the time

BigQuery vs Snowflake Analytics

Compared 7% of the time

Keen IO vs Snowflake Analytics

Compared 6% of the time

Firebolt vs Snowflake Analytics

Compared 5% of the time

Azure Data Factory vs Snowflake Analytics

Compared 5% of the time

More Snowflake Analytics Competitors

Product Reports

Buyer's Guide

AWS Lake Formation

November 2026

Download AWS Lake Formation product report

Buyer's Guide

Snowflake Analytics

October 2026

Download Snowflake Analytics product report

Overview

AWS Lake Formation streamlines data lake organization by integrating seamlessly with AWS services, ensuring robust access control, and facilitating effective data management. Its extensible framework and centralized data handling make it ideal for cloud environments that require scalability.

AWS Lake Formation offers comprehensive data synchronization with AWS, robust security through fine-grained policies, and seamless team collaboration tools. It centralizes data assets, supports analytics with Glue, and enhances data mesh structures. Its IAM integration supports efficient governance, with reliable data storage and retrieval backed by extensive documentation. While highly efficient within AWS ecosystems, Lake Formation faces integration challenges with third-party libraries, and users experience clutter in its interface. Aspects such as automation, policy management, and debugging are areas for improvement. Enhancements in orchestration, cross-account sharing, and integrations with services like SageMaker are user recommendations.

What are the key features of AWS Lake Formation?

Data Synchronization: Integrates with AWS services for seamless data management.
Security Policies: Implements fine-grained access control for secure data handling.
Team Collaboration: Facilitates cooperation through centralized data management.
Analytics Support: Enhances data processing with Glue integration.
Extensibility: IAM integration allows scalable governance.

What benefits or ROI can users expect?

Scalability: Efficiently manages expanding data volumes.
Cost Efficiency: Reduces cloud data management expenses.
Data Security: Ensures compliance with robust policies.
Comprehensive Support: Access to detailed documentation and AWS resources.

Organizations utilize AWS Lake Formation across various industries to build and manage data lakes, ensuring effective data governance and storage solutions. It helps integrate and transform data, control permissions, and support analytics. From e-commerce to healthcare, AWS Lake Formation delivers centralized data repositories for structured and unstructured data, securing information while providing scalable infrastructure and efficient resource management.

Amazon Web Services (AWS)

Snowflake Analytics offers advanced capabilities in data warehousing and cloud data migration, with support for machine learning and business intelligence tasks. Its scalable architecture supports large data volumes while enhancing cost efficiency through decoupled computation and storage.

As a flexible, managed environment, Snowflake Analytics enhances data sharing and integration across multiple cloud platforms. It allows seamless data pipeline creation, supports advanced analytics, and facilitates reporting and visualization. Despite facing integration challenges with legacy systems and complex queries, Snowflake's continuous improvements aim to address these issues, making it a reliable choice for organizations transitioning to the cloud.

What features define Snowflake Analytics?

Time Travel: Enables users to access historical data effortlessly.
Zero-Copy Cloning: Allows cloning of data without storage costs.
Scalability: Easily handles large data volumes.
Data Sharing: Facilitates seamless data sharing across platforms.
Decoupled Architecture: Enhances cost efficiency by separating computation and storage.

What benefits should businesses look for in Snowflake reviews?

Cost Efficiency: Optimized costs through advanced storage management.
Performance: High-speed computations and real-time analytics.
Security: End-to-end encryption ensuring data security.
Flexibility: Supports multiple cloud environments for diverse needs.

Enterprises across industries utilize Snowflake Analytics for its robust data handling and cloud integration capabilities. It serves sectors in need of efficient data warehousing, real-time analytics, and machine learning support, making it suitable for cloud migration and enhancing business intelligence operations.

Snowflake Computing

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper

Buyer's Guide

AWS Lake Formation vs. Snowflake Analytics

November 2026

Free Report: AWS Lake Formation vs. Snowflake Analytics

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