We compared Snowflake and BigQuery based on our user's reviews in several parameters.
Snowflake is praised for its high performance, scalability, and ease of use, as well as its excellent customer service and reasonable pricing. On the other hand, BigQuery stands out for its robust scalability, efficient performance, seamless integration, and positive ROI. BigQuery users have also highlighted exceptional customer service and transparent pricing, while suggesting areas for improvement in optimization, performance, and integrations.
Features: Snowflake's most valuable features lie in its high performance, scalability, and ease of use. Users appreciate its ability to handle large volumes of data efficiently, with seamless scalability and a user-friendly interface. On the other hand, BigQuery is known for its robust scalability and efficient performance. It also offers seamless integration with other Google Cloud services, flexibility in handling large datasets, and a user-friendly interface.
Pricing and ROI: Snowflake's setup cost is appreciated for its reasonable and competitive pricing, straightforward process, and flexible licensing terms. In comparison, BigQuery boasts a minimal setup cost, enabling a quick and hassle-free implementation process, with a fair and transparent pricing structure. Both products accommodate various user needs and requirements., The user reviews indicate that Snowflake's ROI has been positive. BigQuery's ROI, on the other hand, has led to significant cost savings, improved data analysis capabilities, faster query speed, enhanced efficiency, increased productivity, better decision-making processes, and positive business growth.
Room for Improvement: Snowflake could benefit from enhancements to enhance user experience and functionality. User feedback for BigQuery suggests the need for better optimization and performance when handling larger datasets. Improving query execution time, enhancing reliability and stability, expanding integrations and supporting more data sources, simplifying the user interface, and providing intuitive documentation have been recommended for BigQuery to enhance user experience.
Deployment and customer support: The reviews indicate that for Snowflake, it is necessary to evaluate deployment and setup durations separately, considering different amounts of time spent on each phase, while for BigQuery, both deployment and setup durations should be taken into account depending on the context mentioned by users. No specific user quotes were provided for BigQuery., Snowflake's customer service has received positive feedback for its promptness, effectiveness, and expertise in resolving issues. Customers appreciate their responsiveness and willingness to address concerns. In comparison, BigQuery's customer service is highly praised for its responsiveness, helpfulness, and expertise in explaining and solving queries. Overall, both companies offer exceptional customer service and support.
The summary above is based on 71 interviews we conducted recently with Snowflake and BigQuery users. To access the review's full transcripts, download our report.
"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
"The setup is simple."
"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 solution's reporting, dashboard, and out-of-the-box capabilities match exactly our requirements."
"It's straightforward to set up."
"The feature called calibrating the capacity is valuable."
"It stands out in efficiently handling internal actions without the need for manual intervention in tasks like building cubes and defining final dimensions."
"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."
"We find the data sharing and data marketplace aspects of Snowflake absolutely amazing."
"Everything is automatic, and I don't have to do any maintenance."
"The initial setup is straightforward. You just need to follow the documentation."
"The product's most important feature is unloading data to S3."
"The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power."
"It was relatively easy to use, and it was easy for people to convert to it."
"All the people who are working with Snowflake are extremely happy with it because it is designed from a data-warehousing point of view, not the other way around. You have a database and then you tweak it and then it becomes a data warehouse."
"Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
"The processing capability can be an area of improvement."
"The process of migrating from Datastore to BigQuery should be improved."
"I rate BigQuery six out of 10 for affordability. It could be cheaper."
"The product’s performance could be much faster."
"The main challenges are in the areas of performance and cost optimizations."
"There are many tools that you have to use with BigQuery that are different services also provided for by Google. They need to all be integrated into BigQuery to make the solution easier to use."
"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."
"So our challenge in Yemen is convincing many people to go to cloud services."
"I see room for improvement when it comes to credit performance. The other thing I'd like to be improved is the warehouse facility."
"These aren't as crucial, but there are common errors sometimes where the database is down, or a table is nullified and a new table is added and you are not given access to that. With those errors, you don't have permissions."
"Snowflake needs transparency over costs and pricing."
"Their strategy is just to leverage what you've got and put Snowflake in the middle. It does work well with other tools. You have to buy a separate reporting tool and a separate data loading tool, whereas, in some platforms, these tools are baked in. In the long-term, they'll need to add more direct partnerships to the ecosystem so that it's not like adding on tools around Snowflake to make it work. They can also consider including Snowflake native reporting tools versus partnering with other reporting tools. It would kind of change where they sit in the market."
"They don't have any SLAs in place. It would be better if they did."
"It's difficult to know how to size everything correctly."
"The design of the product is easily misunderstood."
"We would like to have an on-premises deployment option that has the same features, including scalability."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 94 reviews. BigQuery is rated 8.2, while Snowflake is rated 8.4. The top reviewer of BigQuery writes "Expandable and easy to set up but needs more local data residency". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". BigQuery is most compared with Teradata, Oracle Autonomous Data Warehouse, Vertica, Apache Hadoop and AWS Lake Formation, whereas Snowflake is most compared with Azure Data Factory, Teradata, Vertica, AWS Lake Formation and Amazon EMR. See our BigQuery vs. Snowflake report.
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