AWS Lake Formation vs BigQuery comparison

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

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

"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."

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

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

"The main thing I like about BigQuery is storage. We did an on-premise BigQuery migration with trillions of records. Usually, we have to deal with insufficient storage on-premises, but in BigQuery, we don't get that because it's like cloud storage, and we can have any number of records. That is one advantage. The next major advantage is the column length. We have some limits on column length on-premises, like 10,000, and we have to design it based on that. However, with BigQuery, we don't need to design the column length at all. It will expand or shrink based on the records it's getting. I can give you a real-life example based on our migration from on-premises to GCP. There was a dimension table with a general number of records, and when we queried that on-premises, like in Apache Spark or Teradata, it took around half an hour to get those records. In BigQuery, it was instant. As it's very fast, you can get it in two or three minutes. That was very helpful for our engineers. Usually, we have to run a query on-premises and go for a break while waiting for that query to give us the results. It's not the case with BigQuery because it instantly provides results when we run it. So, that makes the work fast, it helps a lot, and it helps save a lot of time. It also has a reasonable performance rate and smart tuning. Suppose we need to perform some joins, BigQuery has a smart tuning option, and it'll tune itself and tell us the best way a query can be done in the backend. To be frank, the performance, reliability, and everything else have improved, even the downtime. Usually, on-premise servers have some downtime, but as BigQuery is multiregional, we have storage in three different locations. So, downtime is also not getting impacted. For example, if the Atlantic ocean location has some downtime, or the server is down, we can use data that is stored in Africa or somewhere else. We have three or four storage locations, and that's the main advantage."

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

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

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

"The product’s most valuable feature is its ability to manage the database on the cloud."

"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."

"BigQuery excels at structuring data, performing predictions, and conducting insightful analyses and it leverages machine learning and artificial intelligence capabilities, powered by Google's Duarte AI."

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

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

"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."

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

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

"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."

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

"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."

"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."

"Instead of connecting directly to BigQuery, we connect to GCP, Cloud Run, and then to BigQuery, which is a long process."

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

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

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

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

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

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

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

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