BigQuery Reviews

Name: BigQuery
Brand: Google
Rating: 4 (35 reviews)

4.1 out of 5

35 reviews
100% willing to recommend

What is BigQuery?

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.

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BigQuery is the #5 ranked solution in top Cloud Data Warehouse solutions. PeerSpot users give BigQuery an average rating of 8.2 out of 10. Based on the analysis of the 35 most recent BigQuery reviews, the overall sentiment is positive, with a sentiment score of 7.6. (The highest in the category). BigQuery is most commonly compared to Snowflake: BigQuery vs Snowflake. BigQuery is popular among the large enterprise segment, accounting for 67% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 17% of all views.

Helped 814,649 peers since 2012

Featured reviews

VikashKumar1

Tech lead at Ford Motor Company

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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Mohamed Tahri

Head of Insights and Data Middle East at Capgemini

We implement for customers. We work as a global company and we have 350,000 employees, we serve clients across all industries. There are many use cases. There is no use case that we would only apply in the context of BigQuery and not with Snowflake, or not with Synapse, et cetera. It is use case…

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Pravin Gadekar

Google Cloud Architect at Capgemini

I recommend BigQuery. It offers low costs and is quite easy to use, compared to other options like AWS or Azure. If you're already working within the Google Cloud ecosystem, it's a perfect match. However, if you're primarily focused on data warehousing and need something more accessible, Snowflake might be a better option. The integration with other tools has greatly enhanced our data visualization capabilities. It's tightly integrated across various components. The serverless architecture has been immensely beneficial for our projects. We no longer have to concern ourselves with infrastructure management or maintenance, as everything is automated. It makes our team smaller and alleviates worries about infrastructure or downtime. For a beginner learning to use it for the first time, it's relatively straightforward. I rate it an eight out of ten.

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BigQuery mindshare

As of November 2024, the mindshare of BigQuery in the Cloud Data Warehouse category stands at 9.3%, up from 6.7% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Cloud Data Warehouse

Key learnings from peers

Last updated Nov 5, 2024

Valuable Features

"BigQuery allows for very fast access, and it is efficient in handling large datasets compared to other SQL databases."
"The product's most valuable features include its scalability and the ability to handle complex queries on large datasets."
"The solution is very useful nowadays for keeping a huge number of records."

Room for Improvement

"There is a limitation when copying data directly from BigQuery; it only supports up to ten MB when copying data to the clipboard."
"The product could benefit from improvements in user-friendliness, particularly in terms of the user interface."
"Instead of connecting directly to BigQuery, we connect to GCP, Cloud Run, and then to BigQuery, which is a long process."

Pricing

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