AWS Lake Formation vs BigQuery comparison

Amazon Web Services (AWS) and Google are both solutions in the Cloud Data Warehouse category. Amazon Web Services (AWS) is ranked #7 with an average rating of 8.1, while Google is ranked #4 with an average rating of 8.5. Amazon Web Services (AWS) holds a 5.0% mindshare in CDW, compared to Google’s 7.7% mindshare. Additionally, 85% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Google users who would recommend it.

AWS Lake Formation

Read 21 AWS Lake Formation reviews

1,416 Views
1,317 Comparison Views

85% willing to recommend

BigQuery

Read 42 BigQuery reviews

2,882 Views
2,392 Comparison Views

100% willing to recommend

AWS Lake Formation

BigQuery

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Executive SummaryUpdated on Dec 18, 2024

AWS Lake Formation and BigQuery are competing in the cloud services market, particularly in data management and analytics. BigQuery stands out with its superior feature set, offering robust analytics capabilities, while AWS Lake Formation emphasizes strong data governance and security.

Features: AWS Lake Formation focuses on data lake creation, security, governance, and simplifies access rights management. BigQuery offers high-speed SQL analytics, real-time querying, and machine learning integration. The distinction is in AWS's strong governance compared to BigQuery's advanced analytical capabilities.

Room for Improvement: AWS Lake Formation could enhance real-time analytics and improve its machine learning features. It might also benefit from simplified ETL job setups. BigQuery could lower costs for extensive use cases, refine data governance tools, and offer better integration with non-Google services.

Ease of Deployment and Customer Service: AWS Lake Formation is well-integrated with the AWS ecosystem, offering seamless service integration and extensive support. BigQuery’s serverless architecture allows for quick deployment with minimal configuration. While AWS offers personalized customer service, BigQuery provides extensive documentation and online resources.

Pricing and ROI: AWS Lake Formation is cost-effective with flexible pricing models based on storage needs, potentially offering lower initial setup costs. BigQuery uses pay-as-you-go billing for queries, which might be costlier in high-use scenarios but efficient for variable workloads. AWS provides ROI through efficient data management, while BigQuery offers ROI via enhanced analytical capabilities.

To learn more, read our detailed AWS Lake Formation vs. BigQuery Report (Updated: December 2025).

Buyer's Guide

AWS Lake Formation vs. BigQuery

December 2025

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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

7th

Average Rating

8.0

Reviews Sentiment

5.7

Number of Reviews

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

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.0%, up from 5.0% compared to the previous year. The mindshare of BigQuery is 7.7%, up from 7.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Market Share Distribution
Product	Market Share (%)
BigQuery	7.7%
AWS Lake Formation	5.0%
Other	87.3%

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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Luís Silva

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.

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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 LF-Tag system with granular permissions was key to the project as a functionality of AWS Lake Formation."

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

"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."

"There is no doubt that this place exceeded my expectations with its incredible ambiance, attentive service, and mouthwatering menu."

"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."

"AWS Lake Formation works hand in hand with other products."

More AWS Lake Formation pros

"BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes."

"I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."

"It's similar to a Hadoop cluster, except it's managed by Google."

"As a cloud solution, it's easy to set up."

"The feature called calibrating the capacity is valuable."

"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."

"The initial setup is simple."

"The most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."

More BigQuery pros

Cons

"The main challenge we faced with AWS Lake Formation was related to cross-account sharing. Granting access to other AWS accounts for tables or databases in a different AWS account was somewhat difficult."

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

"If I could improve AWS Lake Formation, I would add more integrations with SageMaker."

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

"Despite following official documentation, configuration problems persisted, requiring weeks of support from multiple AWS engineers to resolve."

"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."

"Information about the pricing, cost, and setup cost of the AWS solutions would be beneficial."

More AWS Lake Formation cons

"It would be beneficial to integrate additional tools, particularly from a business intelligence perspective."

"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."

"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 would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in."

"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."

"We'd like to see more local data residency."

"It can be slower and more problematic compared to other platforms such as Snowflake."

"The process of migrating from Datastore to BigQuery should be improved."

More BigQuery cons

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."

"1 TB is free of cost monthly. If you use more than 1 TB a month, then you need to pay 5 dollars extra for each TB."

"The platform is inexpensive."

"BigQuery pricing can increase quickly. It's a high-priced solution."

"The pricing appears to be competitive for the intended usage scenarios we have in mind."

"We are above the free threshold, so we are paying around 40 euros per month for BigQuery."

"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."

"The pricing is good and there are no additional costs involved."

"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."

More BigQuery pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

Computer Software Company

Manufacturing Company

Retailer

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

13%

Media Company

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	12
Midsize Enterprise	9
Large Enterprise	20

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 do you like most about BigQuery?

The initial setup process is easy.

See all answers

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 ...

See all answers

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...

See all answers

Comparisons

Snowflake vs AWS Lake Formation

Compared 19% of the time

Azure Data Factory vs AWS Lake Formation

Compared 18% of the time

Databricks vs AWS Lake Formation

Compared 15% of the time

Amazon Redshift vs AWS Lake Formation

Compared 15% of the time

Amazon EMR vs AWS Lake Formation

Compared 8% of the time

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Oracle Autonomous Data Warehouse vs BigQuery

Compared 20% of the time

Teradata vs BigQuery

Compared 11% of the time

Snowflake vs BigQuery

Compared 11% of the time

OpenText Analytics Database (Vertica) vs BigQuery

Compared 8% of the time

Azure Data Factory vs BigQuery

Compared 5% of the time

More BigQuery Competitors

Product Reports

Buyer's Guide

AWS Lake Formation

January 2026

Download AWS Lake Formation product report

Buyer's Guide

BigQuery

January 2026

Download BigQuery product report

Overview

AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis.

Amazon Web Services (AWS)

BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. ... You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.

Google

Sample Customers

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

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Buyer's Guide

AWS Lake Formation vs. BigQuery

December 2025

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