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 #8 with an average rating of 8.1, while Google is ranked #3 with an average rating of 8.4. Amazon Web Services (AWS) holds a 4.4% 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

1,793 Views
1,506 Comparison Views

85% willing to recommend

BigQuery

Read 43 BigQuery reviews

3,546 Views
2,872 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: April 2026).

Buyer's Guide

AWS Lake Formation vs. BigQuery

April 2026

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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

8th

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

3rd

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2026, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 4.4%, down from 5.1% compared to the previous year. The mindshare of BigQuery is 7.7%, up from 6.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
BigQuery	7.7%
AWS Lake Formation	4.4%
Other	87.9%

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.

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

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

"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."

"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."

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

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

"AWS Lake Formation lets you see all your data and tables on one screen."

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

More AWS Lake Formation pros

"To be frank, the performance, reliability, and everything else have improved, even the downtime."

"It has a well-structured suite of complimentary tools for data integration and so forth."

"The features I have found most valuable in BigQuery include the query cache, which is good and scales well; it handles huge amounts of data quite well, and the multi-regions feature works well."

"BigQuery can be used for any type of company. It has the capability of building applications and storing data. It can be used for OLTP or OLAP. It has many other products within the Google space."

"One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions."

"The feature called calibrating the capacity is valuable."

"We like the machine learning features and the high-performance database engine."

"The scalability is excellent, as it can handle large datasets and scale up pretty easily as the data volume grows while remaining very reliable with no bugs, glitches, crashes, or freezes."

More BigQuery pros

Cons

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

"The solution could make improvements around orchestration and doing some automation stuff on AWS front automation."

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

"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."

"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."

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

"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."

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

More AWS Lake Formation cons

"So our challenge in Yemen is convincing many people to go to cloud services."

"Sometimes, support specialists might not have enough experience or business understanding, which can be an issue."

"With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery."

"I understand that Snowflake has made some improvements on its end to further reduce costs, so I believe BigQuery can catch up."

"With what I have seen in BigQuery, I had some response times problems, but then it is an analytical database and not a transactional database, so it comes with eventual consistency."

"BigQuery should integrate with other tools, such as Cloud Logging and Local Studio, to enhance its capabilities further and enable powerful and innovative analyses."

"The price is a bit high but the technology is worth it."

"There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans."

More BigQuery cons

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 platform is inexpensive."

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

"The product operates on a pay-for-use model. Costs include storage and query execution, which can accumulate based on data volume and complexity."

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

"The solution's pricing is cheaper compared to other solutions."

"The solution is pretty affordable and quite cheap in comparison to PDP or Cloudera."

"The product’s pricing could be more flexible for end users."

More BigQuery pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Manufacturing Company

Retailer

Government

Financial Services Firm

17%

Manufacturing Company

11%

Computer Software Company

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	13
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 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?

With what I have seen in BigQuery, I had some response times problems, but then it is an analytical database and not a transactional database, so it comes with eventual consistency. I cannot have e...

See all answers

What is your primary use case for BigQuery?

We are mostly dealing with Google solutions such as BigQuery, NoSQL, SQL analytical database, secrets manager, and most of the serverless infrastructure as well, databases. I run SQL queries on Big...

See all answers

Comparisons

Snowflake vs AWS Lake Formation

Compared 13% of the time

Azure Data Factory vs AWS Lake Formation

Compared 12% of the time

Amazon Redshift vs AWS Lake Formation

Compared 12% of the time

Databricks vs AWS Lake Formation

Compared 12% of the time

Amazon EMR vs AWS Lake Formation

Compared 5% of the time

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Oracle Autonomous Data Warehouse vs BigQuery

Compared 15% of the time

Snowflake vs BigQuery

Compared 10% of the time

Teradata vs BigQuery

Compared 10% of the time

OpenText Analytics Database (Vertica) vs BigQuery

Compared 7% of the time

Azure Data Factory vs BigQuery

Compared 4% of the time

More BigQuery Competitors

Product Reports

Buyer's Guide

AWS Lake Formation

April 2026

Download AWS Lake Formation product report

Buyer's Guide

BigQuery

April 2026

Download BigQuery product report

Also Known As

No data available

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

Information Not Available

Buyer's Guide

AWS Lake Formation vs. BigQuery

April 2026

Free Report: AWS Lake Formation vs. BigQuery

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