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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
13th
Average Rating
7.6
Reviews Sentiment
6.9
Number of Reviews
8
Ranking in other categories
No ranking in other categories
BigQuery
Ranking in Cloud Data Warehouse
4th
Average Rating
8.2
Reviews Sentiment
7.3
Number of Reviews
40
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.2%, down from 6.0% compared to the previous year. The mindshare of BigQuery is 7.0%, down from 8.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

Ramesh Raghavan - PeerSpot reviewer
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.
VikashKumar1 - PeerSpot reviewer
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.

Quotes from Members

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

Pros

"AWS Lake Formation lets you see all your data and tables on one screen."
"The solution has many features that are applicable to events such as audits."
"We use AWS Lake Formation typically for the data warehouse."
"AWS Lake Formation works hand in hand with other products."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"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."
"What I like most about BigQuery is that it's fast and flexible. Another advantage of BigQuery is that it's easy to learn."
"The integrated data storage features are good."
"It has a well-structured suite of complimentary tools for data integration and so forth."
"BigQuery has a very nice interface that you can easily learn if you know SQL."
"The query tool is scalable and allows for petabytes of data."
"It's straightforward to set up."
"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
"It's similar to a Hadoop cluster, except it's managed by Google."
 

Cons

"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."
"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."
"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."
"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."
"AWS Lake Formation's pricing could be cheaper."
"If I could improve AWS Lake Formation, I would add more integrations with SageMaker."
"We would like to be able to calibrate the solution to run on top of a raw file."
"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."
"The process of migrating from Datastore to BigQuery should be improved."
"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. You have to actually open a ticket and then follow it up with Google support."
"For greater flexibility and ease of use, it would be beneficial if BigQuery offered more third-party add-ons and connectors, particularly for databases that don't have built-in integration options."
"I understand that Snowflake has made some improvements on its end to further reduce costs, so I believe BigQuery can catch up."
"The product’s performance could be much faster."
"The initial setup could be improved making it easier to deploy."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"The product’s pricing could be more flexible for end users."
"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."
"The price is a bit high but the technology is worth it."
"The pricing is good and there are no additional costs involved."
"The pricing appears to be competitive for the intended usage scenarios we have in mind."
"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."
"One terabyte of data costs $20 to $22 per month for storage on BigQuery and $25 on Snowflake. Snowflake is costlier for one terabyte, but BigQuery charges based on how much data is inserted into the tables. BigQuery charges you based on the amount of data that you handle and not the time in which you handle it. This is why the pricing models are different and it becomes a key consideration in the decision of which platform to use."
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
14%
Manufacturing Company
9%
University
5%
Computer Software Company
17%
Financial Services Firm
15%
Manufacturing Company
11%
Retailer
8%
 

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.
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.
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...
What do you like most about BigQuery?
The initial setup process is easy.
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.
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...
 

Overview

 

Sample Customers

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