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 #13 with an average rating of 7.3, while Google is ranked #3 with an average rating of 8.4. Amazon Web Services (AWS) holds a 5.8% mindshare in CDW, compared to Google’s 6.5% mindshare. Additionally, 71% 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 8 AWS Lake Formation reviews

1,795 Views
1,035 Comparison Views

71% willing to recommend

BigQuery

Read 41 BigQuery reviews

2,734 Views
1,436 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: June 2025).

Buyer's Guide

AWS Lake Formation vs. BigQuery

June 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

13th

Average Rating

7.6

Reviews Sentiment

6.9

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

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2025, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.8%, up from 5.4% compared to the previous year. The mindshare of BigQuery is 6.5%, down from 8.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

Ramesh Raghavan

US South Lead, Accenture AWS Business Group at Accenture

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.

Read full review

Luís Silva

Chief Technical Lead at Human Code

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

"We use AWS Lake Formation typically for the data warehouse."

"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."

"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 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 initial setup is simple."

"BigQuery is a powerful tool for managing and analyzing large datasets. The versatility of BigQuery extends to its compatibility with external data visualization tools like Power BI and Tableau. This means you not only get query results but can also seamlessly integrate and visualize your data for better insights."

"It's straightforward to set up."

"It stands out in efficiently handling internal actions without the need for manual intervention in tasks like building cubes and defining final dimensions."

"Its integration with other tools like Atlan through a Google Chrome extension is highly beneficial."

"Even non-coders can review the data in BigQuery."

"When integrating their system into the cloud-based solutions, we were able to increase their efficiency and overall productivity twice compared with their on-premises option."

"BigQuery has a very nice interface that you can easily learn if you know SQL."

More BigQuery pros

Cons

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

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

"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."

"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."

"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."

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

"Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance."

"They could enhance the platform's user accessibility."

"The processing capability can be an area of improvement."

"The price could be better. Compared to competing solutions, BigQuery is expensive. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. In the next release, it would be better if they improved their AI bot. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them."

"The main challenges are in the areas of performance and cost optimizations."

"Some of the queries are complex and difficult to understand."

"The solution should reduce its pricing."

"There are some limitations in the query latency compared to what it was three years ago."

"When I open many of the Google Cloud products, I am in an environment that I do not feel familiar with; it is a little overwhelming."

More BigQuery cons

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."

"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."

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

"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."

"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."

"Its cost structure operates on a pay-as-you-go model."

"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."

More BigQuery pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Computer Software Company

13%

Manufacturing Company

Government

Financial Services Firm

16%

Computer Software Company

16%

Manufacturing Company

11%

Retailer

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.

See all answers

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.

See all answers

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...

See all answers

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?

I have not used BigQuery for AI and machine learning projects myself. I know how to use it, and I can see where it would be useful, but so far, in my projects, I have not included a BigQuery compon...

See all answers

Comparisons

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Compared 31% of the time

Azure Data Factory vs AWS Lake Formation

Compared 21% of the time

Amazon Redshift vs AWS Lake Formation

Compared 20% of the time

Microsoft Azure Synapse Analytics vs AWS Lake Formation

Compared 8% of the time

Databricks vs AWS Lake Formation

Compared 6% of the time

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Snowflake vs BigQuery

Compared 18% of the time

Oracle Autonomous Data Warehouse vs BigQuery

Compared 17% of the time

OpenText Analytics Database (Vertica) vs BigQuery

Compared 16% of the time

Teradata vs BigQuery

Compared 16% of the time

Dremio vs BigQuery

Compared 6% of the time

More BigQuery Competitors

Product Reports

Buyer's Guide

AWS Lake Formation

June 2025

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Buyer's Guide

BigQuery

June 2025

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

June 2025

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