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AWS Lake Formation vs BigQuery comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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
7th
Average Rating
8.0
Reviews Sentiment
5.7
Number of Reviews
21
Ranking in other categories
No ranking in other categories
BigQuery
Ranking in Cloud Data Warehouse
4th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
42
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 4.9%, down from 5.1% compared to the previous year. The mindshare of BigQuery is 7.8%, up from 7.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
BigQuery7.8%
AWS Lake Formation4.9%
Other87.3%
Cloud Data Warehouse
 

Featured Reviews

Ciro Baldim Guerra - PeerSpot reviewer
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.
Luís Silva - PeerSpot reviewer
Chief Technical Lead at a consultancy with 201-500 employees
Handles large data sets efficiently and offers flexible data management capabilities
The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data. It is kind of difficult to explain, but structured data and the ability to handle large data sets are key features. The data integration capabilities in BigQuery were, in fact, an issue at the beginning. There are two types of integrations. As long as integration is within Google, it is pretty simple. When you start to try to connect external clients to that data, it becomes more complex. It is not related to BigQuery, it is related to Google security model, which is not easy to manage. I would not call it an integration issue of BigQuery, I would call it an integration issue of Google security model.

Quotes from Members

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

Pros

"We have observed measurable benefits in terms of cost savings, time savings, resource savings, and efficiency improvements in our workflows."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"AWS Lake Formation lets you see all your data and tables on one screen."
"AWS Lake Formation works hand in hand with other products."
"The solution has many features that are applicable to events such as audits."
"The integration of AWS Lake Formation with the IAM for authentication and authorization is very good; I didn't have any problems in the setup and thought it was simple."
"The features and capabilities of AWS Lake Formation that I have found most valuable are that it is really convenient to see all the different data assets that were configured and understand who has and what type of service has or does not have access to those services."
"AWS Lake Formation significantly improves the structure of the data mesh, making it superior to previous structures we used."
"Its integration with other tools like Atlan through a Google Chrome extension is highly beneficial."
"It's pretty stable. It's fast, and it is able to go through large quantities of data pretty quickly."
"The setup is simple."
"The most valuable aspect of BigQuery is its ability to handle high data workloads without causing friction with our online systems."
"BigQuery excels at structuring data, performing predictions, and conducting insightful analyses and it leverages machine learning and artificial intelligence capabilities, powered by Google's Duarte AI."
"The solution is very useful nowadays for keeping a huge number of records."
"BigQuery's querying capabilities are very optimized for large datasets."
"BigQuery excels at data analysis. It processes vast amounts of information using its advanced architecture and sophisticated querying capabilities, making it crucial for critical insights and safe for handling sensitive data."
 

Cons

"AWS Lake Formation's pricing could be cheaper."
"You need to have data experience to use the product."
"I haven't seen any measurable benefits from using AWS Lake Formation, such as time saving, resource saving, or efficiency improvements."
"For the end-users, it's not as user-friendly as it could be."
"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."
"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."
"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."
"The initial onboarding process is challenging because creating a plan takes a month to a month and a half to build out."
"When it comes to queries or the code being executed in the data warehouse, the management of this code, like integration with the GitHub repository or the GitLab repository, is kind of complicated, and it's not so direct."
"I rate BigQuery six out of 10 for affordability. It could be cheaper."
"The main challenges are in the areas of performance and cost optimizations."
"We would like to be able to calibrate the solution to run on top of a raw file."
"It would be helpful if they could provide some dashboards where you can easily view charts and information."
"It would be beneficial if BigQuery could be made more affordable."
"I noticed recently it's more expensive now."
"There are some limitations in the query latency compared to what it was three years ago."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"The price could be better. Usually, you need to buy the license for a year. Whenever you want more, you can subscribe to it, and you can use it. Otherwise, you can terminate the license. You can use it daily or monthly, and we use it based on a project's requirements."
"The tool has competitive pricing."
"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."
"I have tried my own setup using my Gmail ID, and I think it had a $300 limit for free for a new user. That's what Google is offering, and we can register and create a project."
"We are above the free threshold, so we are paying around 40 euros per month for BigQuery."
"The pricing is good and there are no additional costs involved."
"Price-wise, I think that is very reasonable."
"The pricing is adaptable, ensuring that organizations can tailor their usage and costs based on their specific requirements and configurations within the Google Cloud Platform."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Computer Software Company
9%
Manufacturing Company
7%
Retailer
6%
Financial Services Firm
15%
Manufacturing Company
14%
Computer Software Company
12%
Media Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise15
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise9
Large Enterprise20
 

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...
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...
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...
What do you like most about BigQuery?
The initial setup process is easy.
What is your experience regarding pricing and costs for BigQuery?
I believe the cost of BigQuery is competitive versus the alternatives in the market, but it can become expensive if the tool is not used properly. It is on a per-consumption basis, the billing, so ...
What needs improvement with BigQuery?
There are areas that could be improved with BigQuery, such as more bolt-on capabilities and the ability to use more bolt-ons for APIs. Having more of a library of connectors would be really benefic...
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
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Find out what your peers are saying about AWS Lake Formation vs. BigQuery and other solutions. Updated: February 2026.
882,410 professionals have used our research since 2012.