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BigQuery vs Snowflake Analytics 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:
 

ROI

Sentiment score
7.4
Organizations experienced improved performance and cost savings after adopting BigQuery, achieving a 75% cost reduction and efficient data management.
Sentiment score
6.1
Snowflake Analytics offers potential 40-50% performance benefits and cost savings, though financial returns vary based on user needs.
 

Customer Service

Sentiment score
7.2
Customers generally find BigQuery support helpful, but integration challenges and resource availability need improvement despite positive responsiveness.
Sentiment score
7.1
Snowflake Analytics receives praise for responsive support, though some suggest improvements in complex issue resolution and occasional delay handling.
I have been self-taught and I have been able to handle all my problems alone.
rating the customer support at ten points out of ten
Recently we had a two-day session where the Snowflake Analytics team provided a demo on Cortex AI and its features.
The technical support for Snowflake Analytics is excellent based on what I have heard from others.
 

Scalability Issues

Sentiment score
8.0
BigQuery offers impressive scalability and efficiency for large data, but may be costly and present integration challenges for smaller users.
Sentiment score
8.0
Snowflake Analytics efficiently manages large data volumes with dynamic cloud scaling, offering superior scalability and cost efficiency versus competitors.
It is a 10 out of 10 in terms of scalability.
The scalability is definitely good because we are migrating to the cloud since the computers on the premises or the big database we need are no longer enough.
Maintaining security and data governance becomes easier with an entire data lake in place, and the scalability improves performance.
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
It supports both horizontal and vertical scaling effectively.
 

Stability Issues

Sentiment score
8.5
BigQuery is highly stable and reliable for cloud data analytics, efficiently handling large volumes with minor issues.
Sentiment score
8.5
Snowflake Analytics is highly rated for its stable and reliable performance, ensuring minimal disruptions and high availability.
Snowflake Analytics has been stable and reliable in my experience.
Snowflake Analytics is stable, scoring around eight point five to nine out of ten.
 

Room For Improvement

BigQuery users face challenges with migration, integration, cost, scaling, user interfaces, and call for better machine learning capabilities.
Snowflake Analytics requires enhancements in ML, cloud, legacy integration, cost transparency, user experience, and performance with large datasets.
BigQuery is already integrating Gemini AI into the data extraction process directly in order to reduce costs.
In general, if I know SQL and start playing around, it will start making sense.
Troubleshooting requires opening each pipeline individually, which is time-consuming.
I would prefer Snowflake Analytics to improve their support response times, as sometimes the responses we receive are not very prompt and ticket assignments may not be timely.
AIML-based SQL prompt and query generation could be an area for enhancement.
If it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it would be even better.
 

Setup Cost

BigQuery offers flexible, pay-as-you-go pricing based on data usage, with low storage costs and adaptable enterprise plans.
Snowflake Analytics offers flexible usage-based pricing impacting cost, with views varying on expense and competitive pay-as-you-go benefits.
Being able to optimize the queries to data is critical. Otherwise, you could spend a fortune.
The price is perceived as expensive, rated at eight out of ten in terms of costliness.
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
Snowflake Analytics is quite economical.
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
 

Valuable Features

BigQuery excels in scalability, performance, cost-efficiency, and integration with Google products, making it ideal for complex data analyses.
Snowflake Analytics provides efficient, secure, and scalable data management, supporting seamless integration and cost-effective analytics with advanced features.
It is really fast because it can process millions of rows in just a matter of one or two seconds.
BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes.
The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data.
Snowflake Analytics supports data security with a single sign-on feature and complies with framework regulations, which is highly beneficial.
Running a considerable query on Microsoft SQL Server may take up to thirty minutes or an hour, while Snowflake executes the same query in less than three minutes.
There are many capabilities which Snowflake Analytics offers that I find valuable, such as the storage and compute engine that allows working with any cloud system such as AWS or Azure, alongside its efficiencies in storage computation and cost-effectiveness, which saves money compared to on-premise systems.
 

Categories and Ranking

BigQuery
Ranking in Cloud Data Warehouse
3rd
Average Rating
8.2
Reviews Sentiment
7.2
Number of Reviews
41
Ranking in other categories
No ranking in other categories
Snowflake Analytics
Ranking in Cloud Data Warehouse
10th
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
41
Ranking in other categories
Web Analytics (2nd)
 

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of BigQuery is 8.0%, up from 7.8% compared to the previous year. The mindshare of Snowflake Analytics is 1.1%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
BigQuery8.0%
Snowflake Analytics1.1%
Other90.9%
Cloud Data Warehouse
 

Featured Reviews

Luís Silva - PeerSpot reviewer
Handles large data sets efficiently and offers flexible data management capabilities
The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data. It is kind of difficult to explain, but structured data and the ability to handle large data sets are key features. The data integration capabilities in BigQuery were, in fact, an issue at the beginning. There are two types of integrations. As long as integration is within Google, it is pretty simple. When you start to try to connect external clients to that data, it becomes more complex. It is not related to BigQuery, it is related to Google security model, which is not easy to manage. I would not call it an integration issue of BigQuery, I would call it an integration issue of Google security model.
Garima Goel - PeerSpot reviewer
Have created secure cloud-based data lakes and improved real-time data processing using integrated AI features
There are many capabilities which Snowflake Analytics offers that I find valuable, such as the storage and compute engine that allows working with any cloud system such as AWS or Azure, alongside its efficiencies in storage computation and cost-effectiveness, which saves money compared to on-premise systems. We also have features such as pre-cached results, Time Travel, and fail-safe, which are very useful for restoring data if deleted accidentally, and the streams and data pipes that facilitate real-time ingestion are great features as well. Snowflake Analytics offers multiple new connectors, allowing me to connect it with Kafka, and with Snowpark, I can work with any programming language such as Python, Java, or Scala for data processing and analysis. The data sharing feature offered by Snowflake Analytics is good because it allows sharing specific sets of data to end customers or users from different Snowflake Analytics accounts without exposing the entire dataset for data security reasons. Snowflake Analytics' support for machine learning models and real-time insights has enhanced significantly. Originally, it wasn't strong in AI/ML, but now it has multiple models and forecasting capabilities, providing good competition to tools such as Databricks and Spark. In BI, I have worked majorly with Microsoft Power BI, and the integration with Snowflake Analytics is very easy. The way we integrate Snowflake Analytics with other on-premise systems just requires the warehouse details, username, passwords, and the account name, along with multiple options such as client ID and credentials for logging in and creating a session. The end-to-end encryption provided by Snowflake Analytics is very important because, in my previous firm, working in finance and investment management, data encryption is necessary due to the sensitive nature of customer data and the involvement of people's money. It's crucial to have encryption in transit and at rest, along with data masking features which Snowflake Analytics offers.
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Top Industries

By visitors reading reviews
Computer Software Company
16%
Financial Services Firm
14%
Manufacturing Company
11%
Retailer
7%
Computer Software Company
16%
Retailer
9%
Financial Services Firm
9%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise9
Large Enterprise20
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise12
Large Enterprise21
 

Questions from the Community

What do you like most about BigQuery?
The initial setup process is easy.
What is your experience regarding pricing and costs for BigQuery?
I believe the cost of BigQuery is competitive versus the alternatives in the market, but it can become expensive if the tool is not used properly. It is on a per-consumption basis, the billing, so ...
What needs improvement with BigQuery?
I have not used BigQuery for AI and machine learning projects myself. I know how to use it, and I can see where it would be useful, but so far, in my projects, I have not included a BigQuery compon...
What is your experience regarding pricing and costs for Snowflake Analytics?
Snowflake Analytics is quite economical. It does not appear to incur significant extra expenses beyond the solution's initial cost. However, a complete pricing analysis is still in progress.
What needs improvement with Snowflake Analytics?
The advantages of Snowflake Analytics outweigh the disadvantages. However, if it offered flexibility similar to Oracle and supported more heterogeneous data sources and database connectivity, it wo...
 

Overview

 

Sample Customers

Information Not Available
Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper
Find out what your peers are saying about BigQuery vs. Snowflake Analytics and other solutions. Updated: September 2025.
868,706 professionals have used our research since 2012.