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AWS Lake Formation vs Snowflake comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 20, 2025

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
13th
Average Rating
7.6
Reviews Sentiment
6.9
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Snowflake
Ranking in Cloud Data Warehouse
1st
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
100
Ranking in other categories
Data Warehouse (1st), AI Synthetic Data (1st)
 

Mindshare comparison

As of June 2025, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.5%, up from 5.6% compared to the previous year. The mindshare of Snowflake is 18.9%, down from 23.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

Ramesh Raghavan - PeerSpot reviewer
Centralized repository, offers various cataloging mechanisms for quick data retrieval but data governance capabilities could be better
There are a couple of areas for improvement with Lake Formation. One of the main challenges, especially when dealing with rich media content, like in MarTech (Marketing Technology) or ad agencies, is its versatility. Some clients feel that Lake Formation doesn’t meet their needs and they tend to prefer competitor products for those specific use cases. The second area for improvement is in data governance. Specifically, Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance. This includes managing the entire data lineage—where the data originated, how it moves, and where it’s currently stored. The visibility of the data as it evolves is crucial, and that’s where more advanced governance capabilities would be beneficial.
Snehasish Das - PeerSpot reviewer
Transformation in data querying speed with good migration capabilities
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses. One key feature is the separation of compute and storage, which eliminates storage limitations. It also has tools for migrating data from legacy databases like Oracle. Its stability and efficiency enhance performance greatly. Tools in the AI/ML marketplace are readily available without needing development.

Quotes from Members

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

Pros

"The most important advantage in using AWS Lake Formation is its ability to connect the data lake to the other technologies in AWS. This is what I advise my clients."
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"AWS Lake Formation works hand in hand with other products."
"The solution has many features that are applicable to events such as audits."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"I can easily move data from cold storage to regular storage."
"We use AWS Lake Formation typically for the data warehouse."
"AWS Lake Formation lets you see all your data and tables on one screen."
"This is the advanced version of the cloud version, so it's really a flexible tool. If you have it implemented at home, you can access it from anywhere."
"In addition to the database, Snowflake also provides ingestion capabilities."
"They separate compute and storage. You can scale storage independently of the computer, or you can scale computing independently of storage. If you need to buy more computer parts you can add new virtual warehouses in Snowflake. Similarly, if you need more storage, you take more storage. It's most scalable in the database essentially; typically you don't have this scalability independence on-premises."
"The platform's most valuable features include its ability to effectively summarize and manage large datasets, allowing multiple teams to analyze and generate insights."
"The integration capabilities of the product are good and you get what you pay for when it comes to Snowflake."
"The snapshot feature is good, the rollback feature is good and the interface is user-friendly."
"The speed of data loading and being able to quickly create the environment are most valuable."
"The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power."
 

Cons

"Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance."
"You need to have data experience to use the product."
"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."
"It falls short when it comes to more granular access control, such as cell-level or row-level entitlements which is a significant drawback for organizations that require precise control over who can access specific rows of data."
"If I could improve AWS Lake Formation, I would add more integrations with SageMaker."
"The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant."
"AWS Lake Formation's pricing could be cheaper."
"For the end-users, it's not as user-friendly as it could be."
"There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was."
"If we can have a feature where the results can be moved to different tabs, so that I can compare the results with earlier queries before applying the changes, it would be great."
"Sometimes it can be tricky to manage multiple environments if you're purely using Snowflake as your scripting and pipeline environment."
"The complexity of the initial setup of Snowflake depends on the use case. However, Snowflake itself, we don't set it up. The difficulty comes from the ingestion patterns, depending on what data I'm putting in, what kind of enrichment, and what additional value we have to add. However, it does tend to get complex because we have a lot of semi-structured data which we need to handle in Snowflake. There have been some challenges."
"More data governance and access control features would be a welcome addition."
"We would like to have an on-premises deployment option that has the same features, including scalability."
"The cost of the solution could be reduced."
"It's not that flexible when compared to Oracle."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"It is on a monthly basis. It is based on your usage. There are no additional costs from the point of the licensing fee. We do give some kind of evaluation to the customers about how much it is going to be. You can decide in Snowflake the virtual machine that you are using for customers. There are several kinds of virtual machines that you can use. It is similar to the clothing sizes: small to extra large. If you need more power in the coming month, you can decide in advance and take a more powerful machine. You can just select it from the platform. You can also decide which machine you want to take for extracting data."
"Snowflake is a cost-effective solution."
"I believe that pricing is reasonable for this solution."
"I have worked with multiple clouds, and cost-wise, it is a bit costlier than others, such as Redshift. Its price should be reduced."
"The price of the solution is reasonable."
"Pricing is approximately $US 50 per DB. Terabyte is around $US 50 per month."
"The pricing is economical as compared to traditional solutions like Oracle and competitive pricing."
"It's expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
14%
Manufacturing Company
8%
Government
6%
Educational Organization
24%
Financial Services Firm
16%
Computer Software Company
10%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about AWS Lake Formation?
It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services.
What is your experience regarding pricing and costs for AWS Lake Formation?
The pricing is expensive compared to OpenStack, but cheaper than other cloud environments. It's middle-of-the-road for regular storage yet very cost-effective when using Amazon Glacier for data.
What needs improvement with AWS Lake Formation?
If I could improve AWS Lake Formation, I would add more integrations with SageMaker. I would have built-in functions that provide statistics for the data when using the GUI, such as SageMaker Insig...
What do you like most about Snowflake?
The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power.
What is your experience regarding pricing and costs for Snowflake?
It is complicated to understand how requests impact warehouse size. Unlike competitors such as Microsoft and Databricks ( /products/databricks-reviews ), Snowflake lacks transparency in estimating ...
What needs improvement with Snowflake?
There is a need for a tool to help me estimate the cost of using Snowflake. Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently r...
 

Also Known As

No data available
Snowflake Computing
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Find out what your peers are saying about AWS Lake Formation vs. Snowflake and other solutions. Updated: June 2025.
856,873 professionals have used our research since 2012.