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 #4 with an average rating of 8.3. Amazon Web Services (AWS) holds a 5.4% mindshare in CDW, compared to Google’s 7.0% 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

2,092 Views
1,758 Comparison Views

71% willing to recommend

BigQuery

Read 41 BigQuery reviews

3,084 Views
2,470 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 2025).

Buyer's Guide

AWS Lake Formation vs. BigQuery

April 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

4th

Average Rating

8.2

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2025, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.4%, down from 5.8% compared to the previous year. The mindshare of BigQuery is 7.0%, down from 8.2% 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.

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VikashKumar1

Tech lead at Ford Motor Company

Easy to maintain and provides high availability

Since I used BigQuery over the GCP cloud environment, I'm not sure whether we can go through internal IDEAs like IntelliJ or DBeaver that we use to connect with databases. Instead of connecting directly to BigQuery, we connect to GCP, Cloud Run, and then to BigQuery, which is a long process. Sometimes, we face some issues, bugs, and defects. We must first connect with a VPN to check data issues while working from home. Then, it allows you to connect to the cloud. After logging into the cloud, it searches for the service we are looking for, and then we go to BigQuery. This is a long process. After that, we analyze the issues in a table. Instead, it would be very helpful if it could provide a tool that we can install on our MacBook or Windows system. Once we open this tool, we can connect directly to the BigQuery server and easily perform tasks.

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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

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

"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 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."

"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."

"The solution has many features that are applicable to events such as audits."

"I can easily move data from cold storage to regular storage."

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

"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."

"The initial setup is straightforward."

"The initial setup process is easy."

"The query tool is scalable and allows for petabytes of data."

"The most valuable aspect of BigQuery is its ability to handle high data workloads without causing friction with our online systems."

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

"BigQuery allows for very fast access, and it is efficient in handling large datasets compared to other SQL databases."

"The solution is very useful nowadays for keeping a huge number of records."

More BigQuery pros

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."

"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."

"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."

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

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

"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."

"I rate BigQuery six out of 10 for affordability. It could be cheaper."

"The solution hinges on Google patterns so continued improvement is important."

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

"We'd like to have more integrations with other technologies."

"An area for improvement in BigQuery is its UI because it's not working very well. Pricing for the solution is also very high."

"The initial setup could be improved making it easier to deploy."

"It would be better if BigQuery didn't have huge restrictions. For example, when we migrate from on-premises to on-premise, the data which handles all ebook characters can be handled on-premise. But in BigQuery, we have huge restrictions. If we have some symbols, like a hash or other special characters, it won't accept them. Not in all cases, but it won't accept a few special characters, and when we migrate, we get errors. We need to use Regexp or something similar to replace that with another character. This isn't expected from a high-range technology like BigQuery. It has to adapt all products. For instance, if we have a TV Showroom, the TV symbol will be there in the shop name. Teradata and Apache Spark accept this, but BigQuery won't. This is the primary concern that we had. In the next release, it would be better if the query on the external table also had cache. Right now, we are using a GCS bucket, and in the native table, we have cache. For example, if we query the same table, it won't cost because it will try to fetch the records from the cached result. But when we run queries on the external table a number of times, it won't be cached. That's a major drawback of BigQuery. Only the native table has the cache option, and the external table doesn't. If there is an option to have an external table for cache purposes, it'll be a significant advantage for our organization."

"When I execute a query, the dashboard doesn't always present the output seamlessly."

More BigQuery cons

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."

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

"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."

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

"Price-wise, I think that is very reasonable."

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

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

"The tool has competitive pricing."

More BigQuery pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

Computer Software Company

13%

Manufacturing Company

Government

Computer Software Company

17%

Financial Services Firm

15%

Manufacturing Company

12%

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?

The price is perceived as expensive, rated at eight out of ten in terms of costliness. Still, it offers significant cost savings.

See all answers

What needs improvement with BigQuery?

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. In general, if I know SQL and start playing around, it will star...

See all answers

Comparisons

Snowflake vs AWS Lake Formation

Compared 35% of the time

Amazon Redshift vs AWS Lake Formation

Compared 19% of the time

Azure Data Factory vs AWS Lake Formation

Compared 18% of the time

Microsoft Azure Synapse Analytics vs AWS Lake Formation

Compared 10% of the time

Amazon EMR vs AWS Lake Formation

Compared 5% of the time

More AWS Lake Formation Competitors

Snowflake vs BigQuery

Compared 20% of the time

Oracle Autonomous Data Warehouse vs BigQuery

Compared 16% of the time

Teradata vs BigQuery

Compared 16% of the time

Vertica vs BigQuery

Compared 14% of the time

Dremio vs BigQuery

Compared 5% of the time

More BigQuery Competitors

Product Reports

Buyer's Guide

AWS Lake Formation

May 2025

Download AWS Lake Formation product report

Buyer's Guide

BigQuery

May 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

April 2025

Free Report: AWS Lake Formation vs. BigQuery

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