Comparison Buyer's Guide

Executive SummaryUpdated on Jul 22, 2024

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Ranking in Cloud Data Warehouse
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Ranking in Cloud Data Warehouse
Average Rating
Number of Reviews
Ranking in other categories
Data Warehouse (1st)

Mindshare comparison

As of July 2024, in the Cloud Data Warehouse category, the mindshare of BigQuery is 6.3%, down from 8.2% compared to the previous year. The mindshare of Snowflake is 30.4%, up from 24.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
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Data Warehouse

Featured Reviews

May 29, 2022
Gave us 27% performance improvement and reduced costs by about 17%
If I'm collaborating with Google Data Cloud, I can use the cache, and I don't have to pay again and again. There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot. There's also the Array function. You can also enable Spark on BigQuery, which is actually faster than any other Spark. If you use Dataproc, Spark on BigQuery is much faster. Spark will actually eliminate the usage of a lot of Adobe legacy things. It will act as a Spark SQL. It is not that cost-friendly, but it is very performance-friendly. There are also machine learning features.
Ankit  Shukla - PeerSpot reviewer
Mar 17, 2023
Options to connect with extendable sources in three buckets comes in handy
Our primary use case for Snowflake is inputting data generated by AWS This solution has helped our organization by being easy to maintain and having good technical support. The features I have found most valuable are the options to connect with extendable sources in three buckets in which we can…

Quotes from Members

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


"What I like most about BigQuery is that it's fast and flexible. Another advantage of BigQuery is that it's easy to learn."
"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
"BigQuery excels at data analysis. It processes vast amounts of information using its advanced architecture and sophisticated querying capabilities, making it crucial for critical insights and safe for handling sensitive data."
"One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions."
"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 setup is simple."
"It has a well-structured suite of complimentary tools for data integration and so forth."
"The most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."
"It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud. It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it."
"Once you have finished your designs they can be easily imported to Snowflake and the information can be readily accessed without an IT expert."
"Snowflake is faster than on-premise systems and allows for variable compute power based on need."
"Time travel is one feature that really helps us out."
"Its performance is most valuable. As compared to SQL Server, we are able to see a significant improvement in performance with Snowflake."
"The most valuable features of Snowflake are its performance and power."
"The most valuable features are the clustering, LS50, being able to change the size, the pay per use feature, the flexibility with many different sources and analytic applications."
"This solution has helped our organization by being easy to maintain and having good technical support."


"The product’s performance could be much faster."
"BigQuery should integrate with other tools, such as Cloud Logging and Local Studio, to enhance its capabilities further and enable powerful and innovative analyses."
"The processing capability can be an area of improvement."
"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."
"The main challenges are in the areas of performance and cost optimizations."
"The initial setup could be improved making it easier to deploy."
"I understand that Snowflake has made some improvements on its end to further reduce costs, so I believe BigQuery can catch up."
"As a product, BigQuery still requires a lot of maturity to accommodate other use cases and to be widely acceptable across other organizations."
"Snowflake has to improve their spatial parts since it doesn't have much in terms of geo-spatial queries."
"The cost efficiency and monitoring of this solution could be improved. It's easy to spend a lot on Snowflake and it does offer monitoring tools but they're pretty basic."
"The design of the product is easily misunderstood."
"There could be better ELT tools that are appropriate for Snowflake. We decided on Matillion and it seemed to be the only one. There need to be better choices, it would be great if Snowflake provided an ELT solution that people could use. Additionally, if there was a pure cloud-based ELT tool it would be useful."
"Currently, Snowflake doesn't support unstructured data."
"In a future release we would like to have a link which would allow us to connect to an external database and create certain views in your own database. This is because it is becoming hard for us to compare the data between multiple sources."
"We would like to be able to do modeling with Snowflake. It should support statistical modeling."
"If they could bring in some tools for data integration, it would be really great."

Pricing and Cost Advice

"The pricing appears to be competitive for the intended usage scenarios we have in mind."
"The product’s pricing could be more flexible for end users."
"Price-wise, I think that is very reasonable."
"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."
"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."
"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."
"Its cost structure operates on a pay-as-you-go model."
"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."
"There is a licensing for this solution and we purchased an enterprise license. Overall the solution is cost-effective."
"Comparing Snowflake to on-prem options such as Oracle or SAP, it seemed more cost-effective."
"Pricing is based on usage. It is the most expensive of our data tools."
"It is pay-as-you-go. Its cost is in the medium range."
"It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive. Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way."
"The tool's pricing is based on the number of queries you want on your database. The cost is small. To get the tool's pricing, you can do the math based on the cost per query, which is $0.002. If you're running your queries frequently, your charges will be higher than running fewer queries."
"The pricing is economical as compared to traditional solutions like Oracle and competitive pricing."
"The solution is expensive."
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Top Industries

By visitors reading reviews
Computer Software Company
Financial Services Firm
Manufacturing Company
Educational Organization
Financial Services Firm
Computer Software Company
Manufacturing Company

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business

Questions from the Community

What do you like most about BigQuery?
The initial setup process is easy.
What needs improvement with BigQuery?
BigQuery should integrate with other tools, such as Cloud Logging and Local Studio, to enhance its capabilities further and enable powerful and innovative analyses.
What do you like most about Snowflake?
The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power.
What is your experience regarding pricing and costs for Snowflake?
The product's price range falls between average to a bit expensive range. I think the tool is worth the money if you use it properly. It is difficult for me to speak about the number of users who u...
What needs improvement with Snowflake?
I don't think that the AI tools in Snowflake are good. AI tools in Snowflake can be improved. Even if the AI tools in Snowflake are good, I feel that it would be expensive. The cost of the AI part ...



Also Known As

No data available
Snowflake Computing



Sample Customers

Information Not Available
Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Find out what your peers are saying about BigQuery vs. Snowflake and other solutions. Updated: July 2024.
792,905 professionals have used our research since 2012.